Intern in Sber's Risk Quants team, creating intelligent risk analysis systems. Work on NLP/LLM models, AI agents, transformer models for banking tasks, and classical ML credit models.
Tasks:
- Development of pricing models and risk metric calculations for financial instruments, as well as approaches to market risk management
- Development of advanced AI methods for finance: generative modeling of multimodal data (diffusion, VAE, LLM, etc.), reinforcement learning
- Combination of fundamental research with applied Sber tasks
Requirements:
- Full-time study, 2nd year or above
- Education with a mathematical focus (preferred)
- Understanding of financial mathematics: probability theory and stochastic processes, mathematical statistics and econometrics
- Proficiency in Python (NumPy, Pandas, PyTorch)
- Basic knowledge of ML/DL
- Classical ML methods, Deep Learning
- Modern generative models / RL algorithms
- LLM architectures and principles
Conditions:
- Comfortable modern office
- Work format — office (hybrid possible)
- Over 400 educational programs from SberUniversity for professional and career development
- Adaptation program and supervisor support at the start
Skills:
- Python
- NumPy
- Pandas
- PyTorch
- ML
- Deep Learning
- LLM
- NLP
- Generative Models
- Diffusion Models
- VAE
- Reinforcement Learning
- Time Series
- Transformer
