About the role
Build and deploy LLM systems and workflows into production environments for banking applications. Evaluate AI performance through offline evaluations, A/B testing, and live monitoring while collaborating with product and risk teams.
What they look for
Requirements
Candidates must be fresh graduates with a degree in a quantitative field and strong Python fundamentals. Experience building LLM-based projects through internships, hackathons, or academic work is required.
Full description
What you'll do:
- Build and ship LLM systems and workflows to production, where real bankers and customers use them
- Learn to evaluate AI properly: offline evals, A/B tests, live monitoring
- Work hands-on with Python, vLLM, prompt optimization, and fine-tuning
- 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:
- Fresh graduate (Bachelor's or Master's) in a quantitative field: Statistics, Computer Science, Math, Engineering, Physics
- Strong Python fundamentals
- Have experience on building something with LLMs (through Thesis, internship, side project, or hackathon) and can explain the concept and its objective in a simple way
Bonus points (not required):
- Exposure to vLLM, LoRA/QLoRA fine-tuning, or prompt optimization frameworks like GEPA
- Interest in financial data and regulation
Similar roles
-
Data Scientist / Senior Data Scientist
Relentless Health, Inc. Menlo Park, California, United States · $160K–$225K/yr
-
Senior Data Scientist (Generative AI)
Razer Inc. Singapore, Singapore
-
Data Scientist - AI Evaluation & Benchmarking Manager
PwC Birmingham, England, United Kingdom
-
Senior Associate - Data Scientist (IND)
Bread Financial Bengaluru, Karnataka, India
- Contractor, AML (Data Scientist), 6 months contract
-
IT Auditor | Data Scientist
coni+partner AG Zurich, Zurich, Switzerland