Vladimir Shulyak
Engineering Manager, Data Science
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolVladimir Shulyak is an engineering manager and entrepreneur with 15 years of experience building ML products end-to-end, currently leading data science efforts for Pricing & Promotions at Delivery Hero in Berlin. He combines hands-on modelling, deployment, and MLOps experience—ranging from forecasting and recommender systems to production orchestration with DVC, Airflow, Kubernetes and TICK stack—with a track record of founding three startups and shipping full-stack platforms. Vladimir has led cross-functional teams at enterprises like Gazprom Neft and in consultancy roles, turning research prototypes into robust production services using tools such as LightGBM, GluonTS and PyTorch. Comfortable switching between product vision and low-level engineering, he’s known for autonomously assembling teams and resolving both business and technical challenges to launch data products from scratch. An understated strength is his hybrid background spanning data engineering, optimization and realtime systems, which helps him bridge gaps between analytics, infra and customer value.
15 years of coding experience
13 years of employment as a software developer
Information Systems, Information Systems at Saint-Petersburg State University Information Technologies, Mechanic and Optics (University ITMO)Mind the Bridge
English, Portuguese, Italian, Russian, German
Github Skills (60)
validation10
pandas-dataframe10
schema10
async9
testing9
data-validation9
pandas9
test-data9
coercion9
hypothesis-testing9
data-cleaning9
client-server9
http-client9
http-server9
aiohttp9
Programming languages (3)
Github contributions (5)
vshulyak/ts-eval
Oct 2019 - Jun 2022
Time Series analysis and evaluation tools
Contributions:3 releases, 35 pushes, 3 tags in 2 years 8 months
time-seriestime-series-analysisevaluation
vshulyak/simd-structts
Aug 2020 - Jan 2021
Multivariate forecasting using StructTS/Unobserved Components model without MLE param estimation.
Contributions:31 commits, 9 PRs, 26 pushes in 4 months
forecastingunobserved-componentsmachine-learningestimationmultivariate
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