AI Data Scientist

Обязанности: Build and validate predictive / ML models for demand and sales forecasting, promo response, price elasticity and scenario (what-if) analysis. Deliver commercial and customer analytics: segmentation, ABC-XYZ, RFM, LTV, churn, cross- and up-sell, assortment and price-matrix analysis. Design and ship GenAI and agentic solutions — document processing (OCR/NLP), retrieval-augmented generation (RAG) over corporate data, copilots and assistants for business and process tasks. Automate routine analytics and reporting through LLM agents and scripting, cutting manual effort across the function. Apply process mining to map business processes, surface bottlenecks and control gaps, and measure cycle KPIs (touchless / STP, first-time-right). Co-design process automations with the Business Process and functional teams; translate findings into clear functional requirements. Build and maintain data pipelines and integrations with source systems (ERP K-Soft / 1С, Qlik Sense); prepare data marts, features and clean datasets. Deploy models into production, monitor performance and retrain; embed model outputs into business processes and Qlik Sense dashboards. Translate ambiguous business questions into well-scoped analytical problems and communicate results to non-technical stakeholders. Document models, data flows and technical specifications; ensure reproducibility and knowledge transfer. Train and support users on analytical tools and AI-assisted workflows. Research and pilot new methods, models and tools; propose where AI/ML creates measurable business value. Требования: 5+ years in data science, machine learning or advanced analytics, with models taken to production. Strong Python (pandas, scikit-learn, and ML/DL frameworks) and SQL; solid data-engineering fundamentals. Hands-on with GenAI / LLMs and agentic tooling — prompt design, RAG, orchestration and evaluation. Practical command of BI / visualisation (Qlik Sense or Power BI) and of integrating models with ERP / analytics systems. Proven commercial or sales analytics and/or business-process analytics (segmentation, forecasting, process mining, automation). Industry, retail or distribution domain experience is an advantage. Education: higher degree in a quantitative field (data science, computer science, mathematics, statistics or engineering). Languages: Russian C2; English B2/C1 (professional working proficiency). Условия: TBD based on interview results