MLOps Coffee Sessions #118 with Olalekan Elesin, Director of Data Platform & Data Architect at HRS Product Solutions GmbH, co-hosted by Vishnu Rachkonda.
// Abstract
You don't have infinite resources? Call out your main metrics! Focus on the most impactful things that you could do for your data scientists. Olalekan joined us to talk about his experience previously building a machine learning platform at Scaleout24.
From our standpoint, this is the best demonstration and explanation of the role of technical product management in ML that we have on the podcast so far!
// Bio
Olalekan Elesin is a technologist with a successful track record of delivering data-driven technology solutions that leverages analytics, machine learning, and artificial intelligence. He combines experience working across 2 continents and 5 different market segments ranging from telecommunications, e-commerce, online marketplaces, and current business travel.
Olalekan built the AI Platform 1.0 at Scout24 and currently leads multiple data teams at HRS Group. He is an AWS Machine Learning Community Hero in his spare time.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
MLOps Swag/Merch
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// Related Links
What Customers Want: Using Outcome-Driven Innovation to Create Breakthrough Products and Services book by Anthony Ulwick: https://www.amazon.com/What-Customers-Want-Outcome-Driven-Breakthrough/dp/0071408673
Empowered: Ordinary People, Extraordinary Products by Marty Cagan:
https://www.amazon.com/EMPOWERED-Ordinary-Extraordinary-Products-Silicon/dp/111969129X
How to Avoid a Climate Disaster: The Solutions We Have and the Breakthroughs We Need by Bill Gates:
https://www.amazon.com/How-Avoid-Climate-Disaster-Breakthroughs/dp/059321577X
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Connect with Olalekan on LinkedIn: https://www.linkedin.com/in/elesinolalekan/
Timestamps:
[00:00] Introduction to Olalekan Elesin
[00:42] Takeaways
[02:52] Situation at Scaleout24
[07:53] Data landscape engineer and architect
[11:27] Depiction of events
[13:53] Platform approach investment
[15:59] Exceptional need or opportunity to the most intense need
[17:41] Long-tail pieces
[22:01] Metrics
[24:15] Nitty-gritty product works
[26:00] Educating people metrics
[30:02] Upskilling fundamentals of the product discipline
[34:05] Investing in AWS
[37:53] Best-of-breed tools
[44:34] Continuous development for AutoML
[47:26] Rapid fire questions
[52:19] Wrap up
