Data Scientist Interne

**Shaping the future of banking with AI: Distilling and optimizing Large Language Models for AI assistants in finance and banking** The integration of financial services with technology has created an overwhelming amount of structured and unstructured data. To turn this into reliable, real-time intelligence, we need efficient and well-optimized language models, not just raw scale. Swissquote's Data Science team offers an internship focused on **distillation, fine-tuning, and parameter-efficient adaptation (e.g. LoRA)** of Large Language Models (LLMs) for production-grade AI assistants. The main objective is to explore, design, and refine model compression and adaptation techniques to build **fast, cost-efficient, and robust** AI assistants tailored to the banking and finance domains. The DS team is integrated into Swissquote's core research group, the Quantitative Research & Solutions (QRS) department, specialized in theoretical and applied research in Quantitative Finance and Data Science. QRS's mission is to provide best-in-class quantitative and AI solutions by performing research to support every division of the bank in need of an analytical and data-driven approach. **By Joining The Team As Data Scientist Intern You Will:** - Prepare and curate financial text datasets for training, fine-tuning, and evaluation - Apply and benchmark **LLM distillation** techniques to build smaller, faster chatbot models - Use **LoRA and other parameter-efficient fine-tuning methods** to adapt LLMs to banking-specific tasks - Design experiments, evaluate model performance, and help integrate optimized models into AI assistant pipelines