59 avsnitt • Längd: 50 min • Månadsvis
Are you tired of spending hours mastering the latest data science techniques, only to struggle translating your brilliant models into brilliant paychecks?
It’s time to debug your career with Value Driven Data Science. This isn’t your average tech podcast – it’s a weekly masterclass on turning data skills into serious clout, cash and career freedom.
Each episode, your host Dr Genevieve Hayes chats with data pros who offer no-nonsense advice on:
• Creating data solutions that bosses can’t ignore;
• Bridging the gap between data geeks and decision-makers;
• Charting your own course in the data science world;
• Becoming the go-to data expert everyone wants to work with; and
• Transforming from data scientist to successful datapreneur.
Whether you’re eyeing the corner office or sketching out your data venture on your lunch break, Value Driven Data Science is here to help you rewrite your career algorithm.
From algorithms to autonomy – it’s time to drive your value in data science.
Visit the show’s website at: www.genevievehayes.com/episodes
The podcast Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm. is created by Dr Genevieve Hayes. The podcast and the artwork on this page are embedded on this page using the public podcast feed (RSS).
Everyone’s talking about AI, but the real opportunities for data scientists come from being in the room where key AI decisions are made.
In this Value Boost episode, technology leader Andrei Oprisan joins Dr Genevieve Hayes to share a specific, proven strategy for leveraging the current AI boom and becoming your organisation’s go-to AI expert.
This episode explains:
Guest Bio
Andrei Oprisan is a technology leader with over 15 years of experience in software engineering, specializing in product development, machine learning, and scaling high-performance teams. He is the founding Engineering Lead at Agent.ai and is also currently completing an Executive MBA through MIT’s Sloan School of Management.
Links
Curiosity may have killed the cat, but for data scientists, it can open doors to leadership opportunities.
In this episode, technology leader Andrei Oprisan joins Dr Genevieve Hayes to share how his habit of asking deeper questions about the business transformed him from software engineer #30 at Wayfair to a seasoned technology executive and MIT Sloan MBA candidate.
You’ll discover:
Guest Bio
Andrei Oprisan is a technology leader with over 15 years of experience in software engineering, specializing in product development, machine learning, and scaling high-performance teams. He is the founding Engineering Lead at Agent.ai and is also currently completing an Executive MBA through MIT’s Sloan School of Management.
Links
Every data scientist knows the sinking feeling: you’ve done brilliant technical work, but your presentation falls flat with stakeholders.
In this Value Boost episode, communications expert Lauren Lang and data analyst Dr Matt Hoffman join Dr Genevieve Hayes to share their go-to pre-presentation checklist to ensure that sinking feeling never happens again.
You’ll walk away knowing:
Guest Bio
Lauren Lang is the Director of Content for Uplevel and is also a Content Strategy Coach for B2B marketers.
Dr Matt Hoffman is a Senior Data Analyst: Strategic Insights at Uplevel and holds a PhD in Physics from the University of Washington.
Links
It’s known as the “last mile problem” of data science and you’ve probably already encountered it in your career – the results of your sophisticated analysis mean nothing if you can’t get business adoption.
In this episode, data analyst Dr Matt Hoffman and content expert Lauren Lang join Dr Genevieve Hayes to share how they cracked the “last mile problem” by teaming up to pool their expertise.
Their surprising findings about Gen AI’s impact on developer productivity went viral across 75 global media outlets – not because of complex statistics, but because of how they told the story.
Here’s what you’ll learn:
Guest Bio
Dr Matt Hoffman is a Senior Data Analyst: Strategic Insights at Uplevel and holds a PhD in Physics from the University of Washington.
Lauren Lang is the Director of Content for Uplevel and is also a Content Strategy Coach for B2B marketers.
Links
Have you ever noticed that software developers are frequently more productive than data scientists? The reason has nothing to do with coding ability.
Software developers have known for decades that the real key to productivity lies somewhere else.
In this quick Value Boost episode, software developer turned CEO Ben Johnson joins Dr Genevieve Hayes to discuss the focus management techniques that transformed his 20-year development career – which you can use to transform your data science productivity right now.
Get ready to discover:
Guest Bio
Ben Johnson is the CEO and Founder of Particle 41, a development firm that helps businesses accelerate their application development, data science and DevOps projects.
Links
Why do some data scientists produce results at a rate 10X that of their peers?
Many data scientists believe that better technologies and faster tools are the key to accelerating their impact. But the highest-performing data scientists often succeed through a different approach entirely.
In this episode, Ben Johnson joins Dr Genevieve Hayes to discuss how productivity acts as a hidden multiplier for data science careers, and shares proven strategies to dramatically accelerate your results.
This episode reveals:
Guest Bio
Ben Johnson is the CEO and Founder of Particle 41, a development firm that helps businesses accelerate their application development, data science and DevOps projects.
Links
Are your data science projects failing to deliver real business value?
What if the problem isn’t the technology or the organization, but your approach as a data scientist?
With only 11% of data science models making it to deployment and close to 85% of big data projects failing, something clearly isn’t working.
In this episode, three globally recognised analytics leaders, Bill Schmarzo, Mark Stouse and John Thompson, join Dr Genevieve Hayes to deliver a tough love wake-up call on why data scientists struggle to create business impact, and more importantly, how to fix it.
This episode reveals:
Guest Bio
Bill Schmarzo, also known as “The Dean of Big Data,” is the AI and Data Customer Innovation Strategist for Dell Technologies’ AI SPEAR team, and is the author of six books on blending data science, design thinking, and data economics from a value creation and delivery perspective. He is an avid blogger and is ranked as the #4 influencer worldwide in data science and big data by Onalytica and is also an adjunct professor at Iowa State University, where he teaches the “AI-Driven Innovation” class.
Mark Stouse is the CEO of ProofAnalytics.ai, a causal AI company that helps companies understand and optimize their operational investments in light of their targeted objectives, time lag, and external factors. Known for his ability to bridge multiple business disciplines, he has successfully operationalized data science at scale across large enterprises, driven by his belief that data science’s primary purpose is enabling better business decisions.
John Thompson is EY’s Global Head of AI and is the author of four books on AI, data and analytics teams. He was named one of dataIQ’s 100 most influential people in data in 2023 and is also an Adjunct Professor at the University of Michigan, where he teaches a course based on his book “Building Analytics Teams”.
Links
In many organisations, data scientists and data engineers exist as support staff. Data engineers are there to make data accessible to data scientists and data analysts, and data scientists are there to make use of that data to support the rest of the business.
But in helping everyone else in the business, data professionals can often forget to help themselves.
However, just as AI and machine learning can be used to help others in the organisation perform their jobs more effectively, there’s no reason why they can’t also be used to help data professionals excel in their own jobs. And as experts in applying these techniques, data scientists are perfectly placed to leverage them.
In this episode, Prof Barzan Mozafari joins Dr Genevieve Hayes to discuss how AI and machine learning are helping data professionals do their jobs more effectively.
Guest Bio
Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and has won several awards for his research at the intersection of machine learning and database systems.
Highlights
Links
In the 2002 movie, Minority Report, the future of data interaction is depicted as Tom Cruise standing in front of a computer monitor and literally grabbing data points with his hands. Data interaction is shown to be as easy as interacting with physical objects in the real world.
This vision of a world where data is accessible to all was considered to be science fiction when Minority Report was first released. But over 20 years later, we are now at a point where technology has become good enough for this to soon become fact. And its data science that’s making this possible.
Or more accurately, it’s the intersection of data science and art.
In this episode, Michela Ledwidge joins Dr Genevieve Hayes to discuss how virtual reality and data science can be combined to create interactive data storytelling experiences.
Guest Bio
Michela Ledwidge is the co-founder and CEO of Mod, a studio specialising in real-time and virtual production, and the creator of Grapho, a VR platform that lets non-technical users examine and manipulate graph data. She is also the writer and director of A Clever Label, a world-first interactive documentary.
Highlights
Links
When it comes to awareness and understanding, what we know and don’t know can be split into four categories: known knowns; unknown knowns; known unknowns; and unknown unknowns. And to quote former US Secretary of Defence Donald Rumsfeld: “If one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones.”
When Rumsfeld made his famous “unknown unknowns” speech, he was referring to military intelligence. But the concept of “unknown unknowns” is just as relevant to data and data science. Those data dark spots, or data gaps, can be a real issue when it comes to data-driven decision making.
In this episode, Matt O'Mara joins Dr Genevieve Hayes to discuss the challenges and risks data gaps present to businesses and the community, and what data scientists can do to help address this issue.
Guest Bio
Matt O'Mara is the Managing Director of information and insights company Analysis Paralysis and is the founder and Director of i3, which helps organisations use an information lens to realise significant value, increase productivity and achieve business outcomes. He is also an international speaker, facilitator and strategist and is the first and only New Zealander to attain Records and Information Management Practitioners Alliance (RIMPA) Global certified Fellow status.
Highlights
Links
The idea of targeted marketing is nothing new. Even before the advent of computers and data science, businesses have always tried to optimise their advertising campaigns by tailoring their advertisements to their ideal buyers.
Data science allowed businesses to become more effective at this targeting. However, it was still necessary for businesses to manually create the advertising content they wanted to share with their target buyers. That is, until recently.
In this episode, Hikari Senju joins Dr Genevieve Hayes to discuss how advances in AI technology have made it possible to generate personalised advertising content, optimised to produce the best results, and what that means for content creators.
Guest Bio
Hikari Senju is the founder and CEO of Omneky, an AI platform that generates, analyzes and optimizes personalised advertising content at scale. He is a Harvard computer science graduate and also co-founded tutoring app Quickhelp, which he later sold to Yup.com.
Highlights
Links
It’s been 12 years since Thomas H Davenport and DJ Patil first declared data science to be “the sexiest job of the 21st century” and in that time a lot has changed. Universities have started offering data science degrees; the number of data scientists has grown exponentially; and generative AI technologies, such as Chat-GPT and Dall-E have transformed the world.
Yet, throughout that time, one thing has remained the same. Most machine learning projects still fail to deploy.
However, it’s not the technical capabilities of data scientists that let them down – those are now better than ever before. Rather, “it’s the lack of a well-established business practice that is almost always to blame.”
In this episode, Dr Eric Siegel joins Dr Genevieve Hayes to discuss bizML, the new “gold-standard”, six-step practice he has developed “for ushering machine learning projects from conception to deployment.”
Guest Bio
Dr Eric Siegel is a leading machine learning consultant and the CEO and co-founder of Gooder AI. He is also the founder of the long-running Machine Learning Week conference series; author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die and the recently released The AI Playbook; and host of The Dr Data Show podcast.
Highlights
Links
For most people, data science is synonymous with machine learning, and many see the role of the data scientist as simply being to build predictive models. Yet, predictive analytics can only get you so far. Predicting what will happen next is great, but what good is knowing the future if you don’t know how to change it?
That’s where causal analytics can help. However, causal inference is rarely taught as part of traditional prediction-centric data science training. Where it is taught, though, is in the social sciences.
In this episode, Joanne Rodrigues joins Dr Genevieve Hayes to discuss how techniques drawn from the social sciences, in particular, causal inference, can be combined with data science techniques to give data scientists the ability to understand and change consumer behaviour at scale.
Guest Bio
Joanne Rodrigues is an experienced data scientist with master’s degrees in mathematics, political science and demography. She is the author of Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights and the founder of health technology company ClinicPriceCheck.com.
Highlights
Links
With all the reports about the spread of misinformation and disinformation on social media, sometimes it feels like one of the biggest threats to democracy is technology. But no technology is inherently good or bad. It’s how you use it that matters. And just as technology has the potential to harm democracy, it also has the potential to enhance it.
In this episode, Vikram Oberoi joins Dr Genevieve Hayes to discuss how he has been using generative AI and large language models (LLMs) to enhance people’s access to NYC council meetings through his work on citymeetings.nyc.
Guest Bio
Vikram Oberoi is a software engineer, fractional CTO and co-owner of Baxter HQ, a boutique early-stage tech product development firm. He also built and operates citymeetings.nyc, an LLM powered tool to make New York City council meetings accessible.
Highlights
Links
Succeeding in stock market investing is all about timing – buying low, selling high and being able to read the signs to determine when things are going to change. But as anyone who’s ever tried to get rich through stock trading can tell you, this is easier said than done.
Given the massive amounts of financial data published each day, for people who aren’t experts in the field, it can be too hard to spot the patterns and keep up with the constant change. As a result, many people are either investing in markets based on guesswork or not investing at all.
This is where AI can help, because there’s nothing that AI does better than finding patterns in large volumes of data. AI has the potential to democratize access to investment insights.
In this episode, Andrew Einhorn joins Dr Genevieve Hayes to discuss how AI can help ordinary investors find better investment opportunities than they could ever manage on their own.
Guest Bio
Andrew Einhorn is the CEO and co-founder of Levelfields, an AI-driven fintech application that automates arduous investment research so investors can find opportunities faster and easier. Before moving into finance, Andrew started his career as an epidemiologist and helped build a pandemic monitoring system for Georgetown Hospital. He also previously co-founded tech company Synoptus, has consulted for NASA and served as an advisor to a $65 billion hedge fund.
Highlights
Links
As a data scientist, there’s nothing worse than devoting months of your time to building a data product that appears to meet your stakeholders’ every need, only to find it never gets used. It’s depressing, demotivating and can be devastating for your career.
But as the old saying goes, “You can lead a horse to water, but you can’t make it drink”. Or can you?
In this episode, Brian T O’Neill joins Dr Genevieve Hayes to discuss how you can apply the best techniques from software product management and UI/UX design to create ML and AI products your stakeholders will love.
Guest Bio
Brian T O’Neill is the Founder and Principal of Designing for Analytics, an independent data product UI/UX design consultancy that helps data leaders turn ML & analytics into usable, valuable data products. He also advises on product and UI/UX design for startup founders in MIT’s Sandbox Innovation Fund; hosts the podcast Experiencing Data; founded The Data Product Leadership Community and maintains a career as a professional percussionist performing in Boston and internationally.
Highlights
Links
Two years ago, no one could imagine the impact generative AI would have on our world, and most of us can’t even begin to imagine the impact the next generation of AI will have on our world two years from now. The only thing that is certain is uncertainty.
But that uncertainty brings with it great opportunities and choices. We can choose to sit back and let the future of AI play out in front of us or engage with this new technology and shape the future of AI and the world as we know it.
In this episode, Dr Eric Daimler joins Dr Genevieve Hayes to discuss his extraordinary work in shaping the future of AI and what that future might look like.
Guest Bio
Dr. Eric Daimler is the Chair, CEO and Co-Founder of Conexus AI and has previously co-founded five other companies in the technology space. He served under the Obama Administration as a Presidential Innovation Fellow for AI and Robotics in the Executive Office of President, as the sole authority driving the agenda for U.S. leadership in research, commercialization, and public adoption of AI & Robotics. He is also the author of the upcoming book The Future is Formal: The Roadmap for Using Technology to Solve Society’s Biggest Problems.
Highlights
Links
Chances are, you’re reading this summary on a device you didn’t build yourself. Why would you? Tech companies can build you a far better device for a much lower cost than you could ever manage alone. As with many other cases in life, this is an example of where it is better to buy than to build.
Yet, in building a data team, many organisations assume the only solution is to build from within. And although this may be the right solution for some organisations, building a solution isn’t right for all.
In this episode, Collin Graves joins Dr Genevieve Hayes to discuss what a bought solution might look like in the data science space, and whether it is right for you.
Guest Bio
Collin Graves is the CEO of North Labs, a leading fractional cloud data analytics firm that helps growing companies become data-driven. Before founding North Labs, he served with distinction in NATO Special Operations during his tenure with the US Air Force. He is also the author of the upcoming Data Revolution: Leading with Analytics and Winning from Day One.
Highlights
Links
When ChatGPT was first released, there was talk it would lead to traditional search engines, like Google, soon becoming obsolete. That was until users discovered generative AI’s one major drawback – it makes stuff up.
Because of the stochastic nature of ChatGPT, it is never going to be possible to completely eliminate hallucinations. However, there are ways to work around this issue. One such way is through leveraging knowledge graphs and retrieval augmented generation (or RAG).
In this episode, Kirk Marple joins Dr Genevieve Hayes to discuss how knowledge graphs and RAG can be leveraged to improve the quality of generative AI.
Guest Bio
Kirk Marple is the CEO and Technical Founder of Graphlit, serverless, cloud-native platform that streamlines the development of AI apps by automating unstructured data workflows and leveraging retrieval augmented generation.
Highlights
Links
For many people, data science is synonymous with machine learning and many data science courses are little more than overviews of the most used machine learning algorithms and techniques.
Where the majority of data science courses fall short is they neglect to bridge the gap between data science theory and business reality, resulting in many data scientists who are technically strong but unable to create value from their work. However, this doesn’t necessarily have to be the case.
In this episode, Douglas Squirrel joins Dr Genevieve Hayes to discuss systems and techniques data scientists and their managers can use to make data science teams profitable.
Guest Bio
Douglas Squirrel has been coding for forty-five years and has led software teams for twenty-five. He uses the power of conversations to create insane profits in technology organisations of all sizes. His experience includes growing software teams as a CTO in startups; consulting on product improvement; and coaching a wide variety of leaders in improving their conversations, aligning to business goals, and creating productive conflict.
Highlights
Links
One of the big promises of data science is its ability to combine multiple disparate datasets to produce value-creating insights. But this is only possible if you can get all those disparate datasets together, in the one location, to begin with. The has led to the rise of the data engineer and the data orchestration platform.
In this episode, Sandy Ryza joins Dr Genevieve Hayes to discuss the impact of the data scientist on the creation of the next generation of data orchestration tools.
Guest Bio
Sandy Ryza is a data scientist turned data engineer who is currently the lead engineer on the Dagster project, an open-source data orchestration platform used in MLOps, data science, IOT and analytics. He is also the co-author of Advanced Analytics with Spark.
Highlights
Links
From BuzzFeed Quizzes to the national census, it’s impossible to get through life without encountering surveys. However, not all surveys are created equal. As with everything else in data science, garbage going in will inevitably lead to garbage coming out.
In this episode, Kyle Block joins Dr Genevieve Hayes to look at practical techniques for designing surveys to ensure they deliver value, as well as approaches to analysing survey results, to maximise that value.
Guest Bio
Kyle Block is Head of Research at Gradient, an analytics agency that combines advanced statistical and machine learning techniques to answer difficult marketing challenges. He holds a Masters in Spatial Analysis from the University of Pennsylvania and has spent his career helping managers use data to make important decisions.
Talking Points
Links
Most people have come to accept that the price of living in a technological world, and its associated convenience, is some loss of data privacy. However, few realise just how much privacy they are giving up.
In this episode, Dr Katharine Kemp joins Dr Genevieve Hayes to discuss data privacy challenges for consumers and data scientists in the age of AI.
Guest Bio
Dr Katharine Kemp is an Associate Professor in UNSW’s Faculty of Law and Justice and Deputy Director of the Allens Hub for Technology, Law and Innovation. Her research focuses on competition, data privacy and consumer protection regulation, including their application to digital platforms.
Talking Points
Links
Decision-making is an essential part of everyday life and one of the main applications of data science is making the decision-making process easier.
However, mostly when data scientists build models, it’s to make a single decision. But in real life, decision-making is rarely that simple.
In this episode, Prof Warren Powell joins Dr Genevieve Hayes to discuss one way in which the decision-making process can become more complicated, in the form of sequential decision problems.
Guest Bio
Warren Powell is the co-founder and Chief Innovation Officer of Optimal Dynamics and a Professor Emeritus after retiring from Princeton, where he was a faculty member in the Department of Operations Research and Financial Engineering. He is also the author of Sequential Decision Analytics and Modelling and Reinforcement Learning and Stochastic Optimization.
Talking Points
Links
According to the Interview Valet 2023 State of Podcast Guesting Annual Report, there are over 380,000 active podcasts in the world right now, with the average podcast episode receiving just 150 downloads within 30 days of its release.
So, for individuals and organisations looking to use podcast marketing to grow their business, just booking podcast guest appearances isn’t enough. It’s necessary to use a targeted strategy based on data.
In this episode, Tom Schwab joins Dr Genevieve Hayes to discuss how Interview Valet uses data to optimise business results in podcast interview marketing.
Guest Bio
Tom Schwab is the founder and Chief Evangelist Officer of Interview Valet and the author of Podcast Guest Profits and One Conversation Away. He is also an engineer whose first job out of college involved running nuclear power plants in the US Navy.
Talking Points
Links
Start-ups and data science go hand in hand, but usually when people think about how data science can help start-ups, it’s with regard to product development and enhancement. However, it doesn’t matter how great a start-up’s product is, if the financials are a mess, the business is going to struggle.
This is where data science can also help start-ups, in the form of financial modelling and analysis.
In this episode, Lauren Pearl joins Dr Genevieve Hayes to discuss her work in helping start-up founders translate their business ideas into maths via financial models.
Guest Bio
Lauren Pearl is a CEO-turned-CFO who helps start-up founders work better with financial data. She holds an MBA from NYU’s Stern School of Business and is the resident start-up finance expert at NYU’s Berkley Centre for Entrepreneurship.
Talking Points
Links
Data science is among the most in-demand skills of the 21st century, with opportunities existing for data scientists to make a difference and earn good money as an employee in a range of industries. Yet there has also never been a better time to be a data science entrepreneur (or datapreneur).
But for data scientists who have never experienced the entrepreneurial life and who are used to the security of a steady pay check, making the transition from employee to entrepreneur may seem like an impossible leap, regardless of how desirable it may seem.
In this episode, David Shriner-Cahn joins Dr Genevieve Hayes to discuss how data scientists can escape the corporate world and make the transition from employee to datapreneur.
Guest Bio
David Shriner-Cahn is the podcast host and community builder behind Smashing the Plateau, an online platform offering resources, accountability, and camaraderie to high-performing professionals who are making the leap from the corporate career track to entrepreneurial business ownership.
Talking Points
Links
Depending on who you speak to blockchain and cryptocurrency are either the way of the future or the scam of the century. But few would be able to tell you what either of them actually is – including among data scientists for whom data and technology are a way of life.
In this episode, Luke Willis joins Dr Genevieve Hayes to demystify blockchains, cryptocurrency and the data behind them.
Guest Bio
Luke Willis is the dApp UX guy. He’s a web3 developer with extensive front end and UX experience. He’s also the founder of the Koin Press where he writes a regular newsletter, hosts the Koin Press podcast and helps others make their dApp ideas a reality.
Talking Points
Links
When data science first became the must-have skill of the 21st century, organisations were fighting to recruit the best and brightest data science talent. But the glory of having a data scientist on staff was often short-lived, as many organisations soon found they didn’t know what to do with them.
Business leaders had been sold the dream of being able to turn their data into business gold but were unable to maximise the value of the data science expertise they had brought in because they couldn’t communicate effectively with their new data science teams.
In this episode, Dr Howard Friedman joins Dr Genevieve Hayes to discuss how adopting a customer mindset can help business leaders capitalise on the hidden value of data.
Guest Bio
Dr Howard Steven Friedman is a data scientist, health economist, and writer with decades of experience leading data modelling teams in the private sector, public sector and academia. He is an adjunct professor, teaching data science, statistics, and program evaluation, at Columbia University, and has authored/co-authored over 100 scientific articles and book chapters in areas of applied statistics, health economics and politics. His previous books include Ultimate Price and Measure of a Nation, which Jared Diamond called the best book of 2012.
Talking Points
Links
Correlation does not equal causation, as anyone who has studied statistics or data science would know. But understanding causality isn’t just important when you’re developing models.
If you’re working in business and want to be recognised for your work, it’s essential to be able to demonstrate causality between what you do and the benefit flowing through to the business.
In this episode, Mark Stouse joins Dr Genevieve Hayes to discuss how data science can be used to comprehend the underlying cause-and-effect relationships in business data.
Guest Bio
Mark Stouse is the CEO of Proof Analytics, an AI-driven marketing analytics platform. Prior to becoming an analytics software CEO, Mark had a successful career in B2B marketing and in 2014 was named Innovator of the Year at the Holmes Report In2 SABRE Awards for his work in tying marketing and communication investment to key business performance metrics.
Talking Points
Links
The insurance sector owes its existence to data and insurers were some of the first companies to utilise data expertise. Yet, being an early adopter isn’t always as great as it seems. And many big insurers are now discovering the challenges of bringing their long-established data systems into the 21st century.
In this episode, Maria Ferrés joins Dr Genevieve Hayes to discuss the complexities of creating order from data chaos in the insurance industry.
Guest Bio
Maria Ferrés is an actuary with extensive experience throughout Europe and Australia, who now specialises in establishing the enterprise data functions of multinational insurers. She is currently the Enterprise Data Officer at trade credit insurer Atradius and she also advises companies within the insurtech space on the use of data to comply with Data Protection laws.
Talking Points
Links
ChatGPT was one of the best things to ever happen to data science – not so much because of what it can do, but because, virtually overnight, it made AI and data science mainstream.
However, while most data scientists now have experience with ChatGPT and other large language model (LLM)-based technologies as end users, few have had experience in building their own LLM-based tools.
In this episode, Dr Mudasser Iqbal joins Dr Genevieve Hayes to discuss the data science behind LLMs and how to go about doing just that.
Guest Bio
Dr Mudasser Iqbal is the Founder and CEO of TeamSolve, a company dedicated to leveraging AI for digital transformation with a sustainable focus. He has extensive experience in Industrial AI, including multiple patents, and was recognised as an MIT Young Innovator. He also played a key role in the growth of his previous start-up, Visenti, and its subsequent acquisition by Xylem Inc.
Talking Points
Links
Despite its conservative reputation, the financial services industry has always been a big adopter of cutting-edge technologies. Dating back more than a century, it’s also been one of the biggest employers of people with technology and data-related skills. But what does the future hold for the use of tech in the financial services industry?
In this episode, Ben Shapira joins Dr Genevieve Hayes to discuss what this future might look like and how technology is being used right now to improve the lives of consumers.
Guest Bio
Ben Shapira is a digital strategist and UX specialist turned tech entrepreneur. He is the founder and Chief Product Officer of Australian fintech start-up Dinero, as well as being a lecturer in the Master of Media and Communication program at Swinburne University.
Talking Points
Links
Data science is only useful if it can create value. And one way that value can be created is by using data to influence decision-making. Yet, to influence decisions, data scientists need to effectively communicate the outcomes of their work – which is something many struggle with. This is because effective data science communication is about more than just rattling off statistics and expecting your end users to piece them together.
In this episode, Dr Selena Fisk joins Dr Genevieve Hayes to discuss how data scientists can improve their communication by using those numbers to tell a story.
Guest Bio
Dr Selena Fisk is a data storyteller and researcher, with a background in education, who now works with the corporate sector to develop data-informed strategies. She is also the author of a number of books, including I’m Not a Numbers Person: How to Make Good Decisions in a Data-Rich World and Data-Informed Learners: Engaging Students in their Data Story.
Talking Points
Links
Pretty much everyone has a retirement plan, but those plans aren’t always robust enough to see you through to the finish line of life. And part of that is a direct consequence of incorrectly applying data science principles to financial modelling.
In this episode, Todd Tresidder joins Dr Genevieve Hayes to discuss the risks and limitations of using data science when planning for retirement.
Guest Bio
Todd Tresidder is a former hedge fund manager who “retired” at age 35 to become a financial consumer advocate and money coach. He now runs the popular retirement planning website FinancialMentor.com and is the author of a range of books on retirement planning and investments including How Much Money Do I Need to Retire? and The Leverage Equation.
Talking Points
Links
If you look at the list of the greatest inventions of the 20th century, you’ll find they all have two things in common. From tea bags to toasters and from cell phones to cellophane, they all take the form of physical objects, and all are, or at least were, protected by patents.
Yet, since the turn of the century, the nature of inventions has changed significantly. And many of the greatest inventions of this century now take the form of computer code or models.
But how do you protect an invention you can’t physically touch?
In this episode, Helen McFadzean joins Dr Genevieve Hayes to discuss the intersection of artificial intelligence and intellectual property.
Guest Bio
Helen McFadzean is a patent and trademark attorney, with a background in artificial intelligence and mechatronics engineering. She has successfully obtained patents, trademarks and designs for businesses in Australia and overseas in a large number of technology areas including machine learning and image classification, automation, smart devices, audio signal processing, embedded software, and control systems.
Talking Points
Links
Most Intro to Machine Learning courses cover supervised learning and unsupervised learning. But did you know there is also a third type of machine learning, which was used in the development of ChatGPT and is likely to become increasingly important in the not too distant future?
In this episode, Prof Michael Littman joins Dr Genevieve Hayes to discuss reinforcement learning – the other type of machine learning – as well as his new book, Code to Joy: Why Everyone Should Learn a Little Programming.
Guest Bio
Prof. Michael Littman is an award-winning Professor of Computer Science at Brown University, specialising in reinforcement learning; is co-creator of the Machine Learning and Reinforcement Learning courses offered as part of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) program; and is currently serving as Division Director for Information and Intelligent Systems at the (US) National Science Foundation. He is also the author of Code to Joy: Why Everyone Should Learn a Little Programming.
Talking Points
Links
Data science sits at the intersection of Computer Science and Statistics, so it comes as no surprise that many of the best data scientists have a computer science or software development background. And those that don’t? Well, there’s a lot they can learn from software developers.
In this episode, Ethan Garofolo joins Dr Genevieve Hayes to discuss techniques from software engineering and software development that you can use to become a better data scientist.
Guest Bio
Ethan Garofolo is a software developer and software architect, specialising in microservice-based projects and using Lean and DevOps principles to make software development teams more effective. He is the author of Practical Microservices: Build Event-Driven Architectures with Event Sourcing and CQRS and runs the Utah Microservices Meetup group.
Talking Points
Links
The saying goes that if you’re not paying for the product, then you are the product. And every time you interact with the digital world, there’s a good chance your data is going to be harvested for some alternative use.
In this episode of Value Driven Data Science, Dr Kate Bower joins Dr Genevieve Hayes to discuss the data rights of consumers and what data scientists need to be aware of when using consumer data.
Guest Bio
Dr Kate Bower is a consumer data advocate for Australian consumer advocacy group CHOICE, following a previous career in academia, where her focus was on qualitative health research.
Talking Points
Links
We all want to live long, happy and healthy lives, and in the age of technology, it comes as little surprise that people are turning to data for help.
Between smart watches, Oura rings and even just fitness apps like Strava, we’re all generating massive quantities of personal health and fitness data each day, sometimes literally in our sleep. But that data is only valuable if it can be converted into useful insights.
In this episode of Value Driven Data Science, Dr Torri Callan joins Dr Genevieve Hayes to discuss how health tech start-ups, such as UAre, are now looking to do just that.
This is the third part of a three-part special focussing on the use of data science in start-ups.
Guest Bio
Dr Torri Callan is the Data Scientist at Australian health tech start-up UAre, as well as working as a data scientist with fintech start-up Spriggy. He has spent the past 5 years setting up AI and automated risk management for leading finance companies in Australia.
Talking Points
Links
Once upon a time, data scientists needed to develop programming skills to rival those of software engineers, and this limited the ability of people without such skills to make use of AI. But recently, this has changed, with the huge number of no-code and low-code tools entering the market.
In this episode, I’m joined by Geo George to discuss how start-ups are leading the way in leveraging such tools, and in the process, helping to make AI and data science available to all.
This is the second part of a three-part special focussing on the use of data science in start-ups.
Guest Bio
Geo George is a director and co-founder of Mayfly Accelerator, a company that helps founders build, grow and scale disruptive start-ups. He is also a start-up founder in his own right and has experience as an executive in the Government sector, with a focus on strategy and risk management.
Talking Points
Links
Many data scientists dream of using their skills to develop ground-breaking AI technology. Yet, few manage to translate their dreams into commercially viable products – or even know where to begin.
In this episode, start-up founder Dr Jeroen Vendrig joins Dr Genevieve Hayes to discuss his experiences in developing AI-driven products, both in an academic setting and in a variety of organisations within the commercial world.
This is the first part of a three-part special focussing on the use of data science in start-ups.
Guest Bio
Dr Jeroen Vendrig is the Chief Technology Officer of ProofTec, an Australian technology start-up specialising in the development of AI-driven software for damage detection and assessment of high value assets. He has over 20 years’ experience in video analytics with world leading R&D labs and has over 25 patents in force.
Talking Points
Links
AI technology has now reached the point where it can potentially damage the reputation of an organisation, if improperly managed. As a result, many data scientists are now becoming very interested in understanding AI ethics and responsible AI.
In this episode of Value Driven Data Science, Chris Dolman joins Dr Genevieve Hayes to discuss strategies organisations and data scientists can apply to de-risk automated decisions, and in doing so, avoid an AI scandal.
Guest Bio
Chris Dolman is the Executive Manager, Data and Algorithmic Ethics at Insurance Australia Group, a Gradiant Institute Fellow and regularly contributes to external research on responsible AI and AI ethics. In 2022, he was named the Australian Actuaries Institute’s Actuary of the Year, in recognition of his work around data ethics, and was also included in Corinium Global Intelligence – Business of Data’s list of the Top 100 Innovators in Data and Analytics.
Talking Points
Links
The launch of Chat-GPT turned the business world upside down and left many people wondering about the future of their careers. How do you compete against AI? One solution is by delivering a superior customer experience.
In this episode, Dasun Premadasa joins Dr Genevieve Hayes to discuss why technical people often trip up when it comes to customer experience and what data scientists can do to overcome these issues.
Guest Bio
Dasun Premadasa is the founder of DASCX, an independent business analyst consultancy that helps businesses with their digital transformations and IT project delivery. He is also the host of the DASCX Show on YouTube.
Talking Points
Links
From social media to electricity grids and the internet itself, we live in a highly interconnected world. But traditional data science techniques don’t adequately allow for the relationships that can exist between data points in such networks. This is where graph data analysis comes into play.
In this episode, Dr Alessandro Negro joins Dr Genevieve Hayes to discuss how data scientists can exploit the natural relationships that exist within network datasets through the use of graph-powered machine learning.
Guest Bio
Dr Alessandro Negro is the Chief Scientist at GraphAware, the world’s #1 Neo4j consultancy, and Managing Director at GraphAware Italy. He is also the author of Graph-Powered Machine Learning and the recently released Knowledge Graphs Applied.
Talking Points
Links
Data science is an in-demand skill. Yet, many data scientists find it challenging to get started in the industry and to differentiate themselves from other data scientists once they find a job.
In this episode, Jonathan Stark joins Dr Genevieve Hayes to discuss how data scientists can find their niche and build a reputation as a data science authority.
Guest Bio
Jonathan Stark is a former software developer who now helps independent professionals make a living while increasing their impact on the world. He is the author of Hourly Billing Is Nuts, the host of the podcast Ditching Hourly and the co-host of The Business of Authority.
Talking Points
Links
“Data science unicorns” are those rare people who “understand the (data) problem they seek to resolve, have the mathematical expertise to analyse the problem and possess the computing skills to covert this knowledge into outcomes.” In fact, they are considered so rare that some people have suggested they don’t really exist. Yet, although nobody is born a data science unicorn, organisations with the right know-how can create them.
In this episode, Dr Peter Prevos joins Dr Genevieve Hayes to discuss his work in creating data science unicorns from water industry subject matter experts around the world.
Guest Bio
Dr Peter Prevos is a civil engineer, social scientist (and amateur magician) who manages the data science function at Coliban Water in regional Australia and runs courses in data science for water professionals. He is also the author of a number of books including Principles of Strategic Data Science and the recently released Data Science for Water Utilities.
Talking Points
Links
Are you familiar with “environmental justice”? It’s all about equitable access to environmental amenities and the equitable distribution of pollution, and has its roots in the American Civil Rights movement of the 1960’s and 1970’s.
In this episode, Robin Rotman and Amber Spriggs join Dr Genevieve Hayes to discuss the environmental justice movement and how open access GIS-based tools are being used to achieve environmental justice in the USA today.
Guest Bio
Robin Rotman is an Assistant Professor of Energy and Environmental Law and Policy at the University of Missouri-Columbia. She is also a qualified lawyer, focussing on energy, environmental, and natural resource issues, and is a Counsel at Van Ness Feldman, a law firm in Washington DC.
Amber Spriggs is a civil engineering Masters student at the University of Missouri-Columbia with a research focus on hydrology, hydraulic engineering, GIS-based risk assessment, and flood insurance policy.
Talking Points
Links
Data scientists are constantly being told of the importance of effective communication for their career success. But this advice typically translates to being able to communicate effectively the results of their work. One aspect of communication that is often overlooked is conversational communication.
In this episode, Julia Lessing joins Dr Genevieve Hayes to discuss the skills and techniques data scientists can combine to make their workplace conversations a lot easier.
Guest Bio
Julia Lessing is the principal actuary and Director of Guardian Actuarial, which specialises in helping clients use data to solve complex people-oriented problems, and runs the Guardian Actuarial Leadership Program and the Easier Conversations course. She is also the host of the We Are Actuaries podcast and has trained and served as a Lifeline phone counsellor.
Talking Points
Links
In December 2022, OpenAI released ChatGPT for public testing and within a week of its launch, the user count exceeded 1 million. For many, ChatGPT provided a first glimpse at what an AI-powered future might look like.
In this episode, Dr Genevieve Hayes is joined once again by Dr David Joyner to discuss the implications of AI-driven technology, such as ChatGPT, for education, business and the world in general, and to finish their discussion of Georgia Tech’s OMSCS program.
This is the second part of a two-part conversation, which began in Episode 9.
Guest Bio
Dr David Joyner is the Executive Director of Online Education and the Online Master of Science in Computer Science at Georgia Tech’s College of Computing. Between 2019 and 2021 he taught a total of 21,768 for-credit college students, more than any other person on the planet. He is also the author of the recently released Teaching at Scale, and co-author of The Distributed Classroom.
Talking Points
Links
What if you could get a Masters degree in Machine Learning for under US$8000, from a top US university, without quitting your day job or moving location? Georgia Tech’s pioneering Online Master of Science in Computer Science (OMSCS) program offers just that.
In this episode, Dr David Joyner joins Dr Genevieve Hayes to discuss OMSCS, the world’s first MOOC-based degree.
This is the first part of a two-part conversation, which is continued in Episode 10.
Guest Bio
Dr David Joyner is the Executive Director of Online Education and the Online Master of Science in Computer Science at Georgia Tech’s College of Computing. Between 2019 and 2021 he taught a total of 21,768 for-credit college students, more than any other person on the planet. He is also the author of the recently released Teaching at Scale, and co-author of The Distributed Classroom.
Talking Points
Links
Ever since Facebook rebranded itself as Meta, the term “metaverse” has entered everyone’s vocabulary, but there’s still a lot of confusion about what it actually is and how it’s likely to affect our lives in the future.
In this episode, Romeo Cabrera Arévalo, a data scientist working in the immersive technology space, joins Dr Genevieve Hayes to answer these questions and more.
Guest Bio
Romeo Cabrera Arévalo is a senior AI and computer vision researcher and engineer at Immersed, “the world’s first professional metaverse.” He is also an AI and tech advisor to the Board of Laboratorio iA, and has lectured in the Masters of Data Science program at the Escuela Superior Politéchnica del Litoral.
Talking Points
Links
Over the past decade, demand for data talent has grown exponentially, and this has had a massive impact on talent acquision in the data space. Employers of data professionals frequently cite talent acquisition as one of the biggest challenges they face in building their internal data capabilties.
In this episode, Dr Genevieve Hayes is joined by data recruiter Joel Robinstein to discuss the data science recruitment landscape, including practical advice for both data scientists and those looking to employ them.
Guest Bio
Joel Robinstein is Head of Clients Services and Operations at Precision Sourcing Australia, where he has over 12 years’ experience working in the data recruitment space. He is also the co-host of the podcast Keeping Up With Data.
Talking Points
Links
The success of data science projects often depends on being able to get stakeholders, from a variety of backgrounds, to work well together. But what if the stakeholders involved come from very different backgrounds and struggle to understand each other – as can be the case with data scientists and engineers?
In this episode, Dr Genevieve Hayes is joined by software engineer turned data scientist Hendrik Dreyer, who has carved a niche for himself by acting as a intermediary between Team Data Science and Team Engineering.
Guest Bio
Hendrik Dreyer is both a qualified data scientist and a qualified engineer. He worked extensively in a range of senior software engineering roles, in both South Africa and Australia, prior to making the transition into data science. He is now the Manager of Analytics Capability at Australia’s largest superannuation fund, AustralianSuper.
Talking Points
Links
Businesses rarely approach data scientists with well-defined problems to solve. Sometimes, the problems businesses devise aren’t appropriate for solving using data science at all. This makes it difficult for data science projects to succeed.
In this episode, Dr Genevieve Hayes is joined by Rob Deutsch to discuss strategies businesses and data scientists can employ to identify data science use cases and maximise their probability of success.
Guest Bio
Rob Deutsch is the Chief Operating Officer of AkuShaper, a company that uses advanced modelling algorithms and software to build better surfboards faster. He is also a data science consultant with Parity Analytic, and previously founded Boxer, which built software for creating better financial models.
Talking Points
Links
Have you ever wondered what your organisation’s Board are thinking, when it comes to data use?
In this episode, Dr Genevieve Hayes is joined by Dr Stuart Black to discuss the attitudes of Boards to data use and their implications for the organisations they govern.
Guest Bio
Dr Stuart Black is an Enterprise Fellow in data, analytics, disruption and innovation at the University of Melbourne. Prior to joining academia, Stuart spent 30 years in professional services and industry, at employers including Deloitte, where he was Senior Partner, National Australia Bank and AT Kearney. He is also a co-author of the recently released book Business Model Transformation – the AI and Cloud Technology Revolution.
Talking Points
Links
We all know what it means for a human to discriminate against another human, but the concept of a predictive model or an artificial intelligence is relatively new. What does it mean for a model or an AI to discriminate against someone?
In this episode of Value Driven Data Science, Dr Genevieve Hayes is joined by Dr Fei Huang to discuss the importance of considering fairness and avoiding discrimination when developing machine learning models for your business.
Guest Bio
Dr Fei Huang is a senior lecturer in the School of Risk and Actuarial Studies at the University of New South Wales, who has won awards for both her teaching and her research. Her main research interest is predictive modelling and data analytics, and has recently been focussing on insurance discrimination and pricing fairness.
Talking Points
Links
Fei’s papers on fairML and insurance pricing:
The two most challenging transitions you can make in your career are transitioning from individual contributor to team lead, and moving from team lead to managing managers. This is true across all professions, but is particularly pronounced in technical fields, like data science.
In this episode, host Dr Genevieve Hayes is joined by guest Tim Davey to discuss the challenges faced by data scientists looking to climb the corporate ladder, and how employers of data professionals can support them in developing their careers.
Guest Bio
Tim Davey has spent the majority of his career working in the organisational development and HR space where his work has focussed strongly on the development of leaders and working with individuals to understand and maximise their careers. This has included, among other things, providing executive coaching to senior management across a wide range of industries, including media, the performing arts, manufacturing, financial services, transport, education, insurance, legal, and not-for-profit sectors.
Yet, Tim also has a strong technical background himself, having completed a Science degree at the University of Melbourne, and starting his working career in the chemical manufacturing sector, so has first-hand understanding of the challenges faced by the members and leaders of technical teams.
Talking Points
Links
Data presents incredible opportunities for organisations to create value, but with the current skills and labour shortages that are affecting all businesses, finding and retaining data scientists and other data professionals can be hard.
In this episode, host Dr Genevieve Hayes is joined by guest Amanda Aitken to discuss a practical way in which organisations can address the skills shortage, gain much needed data skills and increase staff retention – by upskilling their existing staff.
Guest Bio
Amanda Aitken is a fully-qualified actuary who is currently an educator with the Actuaries Institute of Australia. She teaches data analytics and data science to actuaries through the Actuaries Institute’s Data Analytics Application course and is also a member of the Institute’s Data Analytics Practice Committee and Data Analytics Education Faculty.
Talking Points
Links
En liten tjänst av I'm With Friends. Finns även på engelska.