Director of Quantitative Research

Location: Москва Sber Global Markets is seeking a **Director of Quantitative Research** to build from scratch an adaptive research platform that combines quantitative finance with modern AI/ML methods. The key objective is to build a pipeline for autonomous hypothesis generation and testing, experimentation, and deployment of investment strategies to production. The role entails full ownership of the research agenda, platform architecture, team building, infrastructure development, and engagement with leading research laboratories. Обязанности * **Investment Pipeline Development:** Design and build scalable infrastructure (research and backtesting frameworks) for autonomous hypothesis generation, simulation, and validation of trading strategy code under realistic market conditions, with systematic model refinement and knowledge accumulation. * **AI/ML Research Leadership:** Define research directions and develop AI research methodology. Identify and integrate promising methods and models to extract investment alpha using multi-agent systems and LLMs. * **Full-Cycle Research Management:** Lead the full cycle — from mathematical modeling and data analysis to independent validation of investment strategy code and deployment of validated strategies to production. * **Team Building and Partnerships:** Build a top-tier team of quantitative researchers and data engineers. Develop partnerships with leading AI laboratories. Требования * **Required Experience:** 7–10+ years of experience in quantitative research at leading investment funds or quantitative/quant divisions of investment banks. 3–5 years of research team management experience. * **Proven Track Record:** Development and successful deployment of algorithmic alpha models to production. Experience with multi-agent systems and LLMs is a plus. * **Expertise:** Deep understanding of Equities, FX, Commodities, and/or derivatives markets. Experience with the Russian market is a plus; for candidates with international experience, the ability to rapidly adapt models to the local specifics of the Russian market is important. * **Technical Skills:** Strong understanding of the modern development stack and high-performance computing architecture. * **Education:** PhD or MSc in Mathematics, Physics, Computer Science, Quantitative Finance, or a related field from leading international or Russian universities.