Vadim Nikulin

Data Science Lead @Flo Health

I started my career in Tensor, Russia which is the leading company for tax reporting in Russia now. Then I moved to Yandex where I was working on an AB-testing system in the Search department. After some time of backend engineering I converted to a machine learning team. Our goal was to perform the best search result page having answers from all the sources of different types. My next career step was Facebook where I was working in the Integrity team. This team was responsible for protecting users in critical life situations. Besides core ML technology I'm interested in building end-2-end ML solutions for faster experimenting and producing more robust results. In Flo I’m responsible for the Health team, we’re working on better understanding of women health insights which includes a wide range from infrastructure to adoption of new signals.

Sponsored Case Study

ML Maturity: Unifying and Measuring Processes Across Multiple Teams.

Flo is an AI-driven company. We use machine learning in nearly every part of our product, from cycle predictions to automatic moderation in the community. Our models span years of development, changing architectures, data sources, and frameworks. To support such diverse and long-running tasks, we develop ML infrastructure and common principles that allow us to reduce time to production by up to 80 percent. In this speech, we describe some of our approaches and tools, which address: Computational resources for ML engineers, Unified development environment, Data protection, Model registry, Metric tracking, Experiment reproducibility and other.

Date

Tuesday Nov 9 / 12:10PM PST (45 minutes)

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