A stealth-stage firm fusing advanced AI with deep financial domain expertise to reshape how institutional capital moves and prices risk.
AI Data Scientist - Fixed Income & Capital Markets
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This team is building a computational engine that ingests sprawling, unstructured fixed-income data—yield curves, issuance patterns, dealer runs, macro feeds—and turns it into actionable market intelligence. They’re not wrapping a thin layer of ML around a terminal; they’re architecting models that understand the latent structure of bond markets, from sovereign debt to credit, and reason across time horizons that matter to portfolio managers and trading desks. You’ll design experiments on top of vector-native architectures, train models that learn from decades of fragmented market history, and ship signals that sharpen pricing, risk assessment, and relative-value discovery. The work sits at the intersection of quantitative finance and frontier AI, demanding fluency in both the math of markets and the machinery of modern deep learning.
What they're looking for
- 10+ years of hands-on quantitative modeling experience, with substantial exposure to fixed-income products such as Treasuries, corporates, municipals, or structured credit.
- Deep proficiency in Python and at least one of R, C++, or Julia, with a track record of deploying production-grade models on AWS, GCP, or Azure.
- Comfort working with vector databases and embedding-based retrieval for high-dimensional, non-tabular financial data.
- Strong published or proprietary research history in areas like term structure modeling, credit risk, market microstructure, or macro forecasting.
- Clear-eyed communicator who can explain convexity adjustments and attention mechanisms with equal precision to quants, engineers, and senior stakeholders.