Research
Develops quantitative models for portfolio optimization, fixed income relative value, risk estimation, and AI agents for credit research and portfolio management at a fintech platform. Requires Python coding, quant background, and bachelor's/PhD in math-related field.
About the job
Responsibilities
- Run 100K+ variable portfolio optimizations in seconds.
- Develop machine learning models to estimate relative value and future outperformance in fixed income securities.
- Develop risk models to estimate the tracking error between portfolios.
- Build AI agents to automatically perform credit research, automatically build custom portfolios, and automate other core portfolio management tasks.
Requirements
- Quant researcher or quant trader background (strong candidates from outside quant trading also considered).
- Bachelor’s degree or PhD in Mathematics, Physics, Statistics, Economics, or Computer Science.
- Production-grade code in Python.
- Willing and able to figure stuff out independently.
- Excited to work closely with customers (researcher also acts as own product manager).
Nice-to-Haves
- Fixed income quantitative research.
- Numerical optimization.
- Factor/risk models.
- Polars.
- Machine learning pipelines.
- Multi-modal LLMs.
Compensation
- Base salary: $200K to $325K.
- Aggressive initial equity grant.
- Annual performance-based equity bonuses.
- Health, dental, and vision coverage.
- $150 monthly gym stipend.
- Free lunch and dinner.
Skills
Python, Machine Learning, Numerical Optimization, Polars, Factor Models, Risk Models, Multi-Modal Llms
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