Remote Quantitative Researcher — Portfolio Optimization & Risk

Anemoi Predictive Technology LLC.; Tucson (AZ); Remote; USD 185,000 - 255,000; Full time

Benefits offered by this job

Medical, dental, and vision plan

401(k) plan with company matching

Remote-work equipment and home-office

Annual learning, conference, and pro‑f

Paid parental and caregiver leave

Job summary

Anemoi Predictive Technology LLC in Tucson, AZ is seeking a fully remote Quantitative Researcher for Portfolio Construction. You will build allocation methods, portfolio constraints, concentration limits, turnover controls, and stress diagnostics while maintaining year-round coverage in Mountain Standard Time.

Qualified candidates have 4+ years of experience in quantitative research, strong Python and optimization skills, and the ability to communicate model tradeoffs to researchers and traders.

Qualifications

• Experience with portfolio optimization and risk models.
• Strong numerical Python and optimization skills.
• Ability to explain model tradeoffs to researchers and traders.
• Preferred: experience with transaction-cost-aware optimization.
• Preferred: knowledge of production controls for constrained portfolios.
• Experience collaborating across time zones while maintaining the operating coverage assigned to the Tucson, AZ opening.

Responsibilities

• Develop allocation and risk-budgeting methods
• Model factor, sector, liquidity, and concentration constraints
• Measure turnover, capacity, and stress behavior
• Create transparent diagnostics for portfolio decisions
• Own portfolio constraints, exposure diagnostics, and stress review during year-round Mountain Standard Time coverage through changing national market schedules.

Skills

Python

Optimization

Portfolio optimization

Risk models

Communication

Tools

Python

Job description

Anemoi Predictive Technology LLC in Tucson, AZ is seeking a fully remote Quantitative Researcher for Portfolio Construction. You will build allocation methods, portfolio constraints, concentration limits, turnover controls, and stress diagnostics while maintaining year-round coverage in Mountain Standard Time.

Qualified candidates have 4+ years of experience in quantitative research, strong Python and optimization skills, and the ability to communicate model tradeoffs to researchers and traders.