Summary
Svetlana Vinogradova is a Senior Data Scientist with a decade of expertise in machine learning, applied statistics, and end-to-end model delivery across batch and real-time systems. She has led cross-functional teams to launch customer-facing recommendation engines, clinical algorithms for blood pressure trends, and safety evaluation frameworks for LLM-driven patient interactions, consistently turning analytics into product and investment decisions. Her background in bioinformatics and a PhD-style research trajectory underpin rigorous experimentation, causal inference, and reproducible data engineering practices. Comfortable mentoring practitioners, she teaches tidyverse workflows part-time and has repeatedly built data functions from scratch—combining academic publications and production code to drive user acquisition and clinical impact. Notably, she blends domain depth in healthcare with large-scale consumer analytics, enabling both compliant model governance and measurable business outcomes.
8 years of coding experience
11 years of employment as a software developer
Lomonosov Moscow State University
French, Russian, English, German