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What you'll do:
- Lay the foundation of ML development in the company: experiment tracking, reproducibility, model release, and quality monitoring;
- Exploratory analysis on ClickHouse data (raw and curated layers) — trends, anomalies, and a clear picture of what powers the Intelligence product;
- Design, train, and iterate models for Intelligence scenarios inside user cabinets: analytics and predictive product metrics (scoring, churn, forecasting, anomaly detection), personalization, and guided action scenarios;
- LLM interface on top of analytical data: prompt design, evaluation, answer validation against ClickHouse and curated corporate data, with strict access-control compliance;
- Feature engineering primarily in ClickHouse via SQL (aggregates and materialized views), avoiding unnecessary large-scale exports out of the cluster;
- Ship minimal viable models; validate product impact versus heuristics and strong baselines;
- Offline evaluation and online experiments (A/B or equivalent) on real traffic or users before full-scale rollout;
- Partner with data engineers when new sources land or schemas evolve;
- Align with BU product teams on hypotheses and priorities.
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What we expect:
- Strong Python for ML and analytics;
- Advanced SQL for analytical extracts and feature engineering in ClickHouse (aggregations, window functions, performance-aware query design);
- Hands-on ClickHouse experience: table design, sorting keys, indexing, aggregates, materialized views;
- Hands-on experience with Pandas, NumPy, and scikit-learn — training, validation, interpretation, and product-aligned metrics;
- Solid probability and mathematical statistics; hypothesis testing and A/B or quasi-experiments;
- Understanding of common ML algorithms and their limitations;
- Understanding of columnar analytical databases;
- End-to-end experience shipping ML models to production (from data to serving), including environments without a pre-existing ML-Ops stack;
- MLflow, DVC, or equivalent for reproducible experiments and clean handoff to engineering;
- Understanding of version control systems (Git) and experience using Git in team-based development;
- Hands-on experience with AI and LLM models via APIs — prompting, model comparison, and output-quality checks for Intelligence-style scenarios grounded in ClickHouse and curated corporate data.
- Nice to have:
Experience with RAG, embeddings, or fine-tuning.
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We offer:
- Work in the international company;
- Hybrid working format (office/home office);
- Corporate education — courses and trainings;
- Voluntary health insurance after probation period;
- Effective onboarding program for a better start;
- Corporate events and team buildings.
Senior Data Scientist
Mitgo is a global tech company focused on delivering innovative solutions and promoting entrepreneurship. Our purpose is to build, invest in, and nurture online businesses. Mitgo offers solutions and services in the MarTech, FinTech, Smart Shopping and IT-driven Startup Incubation sectors. We are looking for a Senior Data Scientist to strengthen the IT team that is developing our new corporate services.