LOCATIONS: STOCKHOLM | BANGALORE | MILAN

Session Outline

Argo Workflows is probably the most important tool in our data science and MLOps stack at Oda. Our data scientists use it extensively for everything from data and machine learning pipelines to simulation jobs and route optimization. If it runs as a container, it can run on Argo Workflows. Let us tell you why we love it and show you how we use it!

Key Takeaways

  • What is Argo Workflows and how does it fit into an MLOps stack?
  • What do we use Argo Workflows for at Oda?
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Speaker Bio

Kjetil Åmdal-Sævik – Data Science Manager & Machine Learning Engineer | Oda

Kjetil has been drawn towards the possibilities of solving problems with data and algorithms ever since he started working within business intelligence straight out of school in 2014. After quickly segueing into the back then somewhat mysterious field called data science and spending a few years consulting and leading a data science team within the consumer electronics sector, he finally found himself at Oda in 2019 to be a part of building the future of grocery shopping and logistics with AI. Since then he has been a hands-on data scientist in various places in the company, working with product recommendations, forecasting, and production optimization algorithms, as well as infrastructure and internal tooling for data science and ML. Recently he has transitioned into a more management-oriented role where tries to help the company at large and its data scientists truly unleash the potential in data and AI.

October 14 @ 14:30
14:30 — 14:50 (20′)

Day 1 | M3 | Data Engineering Stage

Kjetil Åmdal-Sævik – Data Science Manager & Machine Learning Engineer | Oda