War Stories Productionising ML // Nick Masca // Coffee Session #35

Coffee Sessions #35 with Nick Masca of Marks and Spencer, War Stories Productionising ML.

//Abstract
A conversation with MLOps war stories. Better said, a war story conversation. The kind that informs modern MLOps best practices.  

Nick shared how to make MLOps organizational changes at large companies. I loved one tidbit he mentioned--"it's an evolution, not a revolution". That's a frank observation about the speed of practical change. As we all know it doesn't happen overnight.  

Another great learning Nick shared focused on the value of delivering incremental results regularly. Oftentimes, ML projects suffer because of a focus on delivering too much too soon. This can then lead to a trough of disappointment with the way things actually pan out. Nick shared his experience on how to avoid such pitfalls with us so you don't have to learn the hard way.

//Bio
Nick currently serves as a Head of Data Science at Marks and Spencer, a large retailer based in the UK.  With a background originally in statistics, he transitioned into data science in 2014 and has picked up many battle scars and learnings since.

//Link to the MLOps War Stories
https://www.linkedin.com/posts/dpbrinkm_what-is-your-mlops-war-story-activity-6772604800971370496-LxtX

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Connect with Nick on LinkedIn: www.linkedin.com/in/nick-masca-09454956/

Timestamps:
[00:00] Introduction to Nick Masca
[01:36] Nick's background in tech
[05:01] Nick's current job
[06:19] Building the basics
[08:18] "If you can gain trust and demonstrate value early, you could also freeze you up to the tidy marks later."
[09:19] Strategy on long-running vision
[10:25] "Historically, the legacy waterfall processes in the business where teams have specialist responsibilities."
[11:14] KPI's
[12:36] KPI translations into action plans
[15:43] Data scientists call
[17:13] Nick's nightmarish story  
[22:52] Making the case on such a nightmarish story
[25:06] Tools used by Marks and Spencer in 2015  
[27:15] More complicated process
[28:08] Takeaways from experience
[30:57] Obstacles in deploying
[34:53] Simplifying models
[37:31] Combining environments into one
[38:45] "Having written standards can be quite helpful to take ownership and responsibility around that."  
[40:23] M&S team interaction
[41:31] "It's an evolution, it's not a revolution I'd say at the moment but there's definitely real emphasis where we are to improve things and work towards goals to enable our team to work quicker, empower them."
[42:10] Team moralizing
[43:11] Takeaways from war stories
[43:30] "The biggest takeaway for me is to start small, keep things simple, try things and it can be surprising sometimes what you'll find. Something simple can give you surprising results."
[44:35] Opinions on Data Science and Machine Learning businesses democratize and commoditize