Quant Researcher: Macro Credit & Structured Alpha

Selby Jennings; New York (NY); On-site; USD 180,000 - 250,000; Full time

Job summary

Selby Jennings is seeking a Quantitative Researcher to drive alpha research across mortgage and structured credit markets. You will develop and implement systematic and discretionary research initiatives spanning Agency/Non-Agency MBS, ABS, RMBS, CMBS, TBA, mortgage derivatives, and credit indices, with direct impact on portfolio construction.

The role requires 3+ years in quantitative research, strong Python skills, and a track record applying advanced statistics to financial markets;

Qualifications

• 3+ years of quantitative research or alpha research in mortgages or securitized products.
• Proven ability to generate investment ideas across MBS, ABS, RMBS, CMBS, and credit indices.
• Deep understanding of mortgage market structure, prepayment modeling, and fixed income analytics.
• Experience applying advanced statistical or ML techniques to financial markets.

Responsibilities

• Generate and develop alpha signals across mortgage and structured credit markets.
• Build predictive models leveraging market, economic, consumer, housing, rates, credit, and alternative data sets.
• Backtest and evaluate alpha signals and strategies with risk analysis.
• Collaborate with Portfolio Managers and Traders to translate research into actionable strategies.

Skills

Python programming

Statistical analysis

Quantitative research

Backtesting

Cross-asset research

Education

Master's or PhD in Mathematics/Statistics/Physics/CS/Economics/Finance

Tools

Pandas

SQL

ML libraries

Job description

Selby Jennings is seeking a Quantitative Researcher to drive alpha research across mortgage and structured credit markets. You will develop and implement systematic and discretionary research initiatives spanning Agency/Non-Agency MBS, ABS, RMBS, CMBS, TBA, mortgage derivatives, and credit indices, with direct impact on portfolio construction.

The role requires 3+ years in quantitative research, strong Python skills, and a track record applying advanced statistics to financial markets;