Data Scientist

What you'll do

Own production AI systems and LLM workflows end to end: design, build, deploy, monitor Build the evaluation layer that decides what ships: offline evals, A/B tests, live monitoring Optimize inference with vLLM, prompt optimization frameworks, and fine-tuning (LoRA/QLoRA) Work alongside experienced teams in Product, Risk, and Compliance to apply data science techniques to real-world banking scenarios, including credit risk and regulatory compliance.

We’re looking for curious and eager-to-learn candidates who are: Having 3+ years experiences on building ML or AI systems, including at least one LLM or RAG system you took to production Skilled in translating technical trade-offs into actionable insights for non-technical stakeholders (for example: Product, Risk, CX, and Compliance) Strong Python fundamentals Proven experience in conducting evaluations that directly influenced key product decisions Bonus points (not required): Banking or fintech background High-throughput LLM serving with vLLM GEPA or similar prompt optimization in practice Fine-tuning for financial use cases