Quant Portfolio Architect: Overlays & Python

Farther; United States; On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health benefits

401(k) matching

Roth IRA options

Unlimited PTO

Job summary

Farther is a rapidly growing RIA blending traditional wealth management with fintech and cutting-edge technology. We are expanding our asset management team to build quantitative overlays and research-driven investment capabilities using Python.

As part of the team you’ll design, backtest, and implement options-based overlays across equity and fixed income, working closely with PMs and engineers to scale research into production-ready platforms with robust risk controls.

Qualifications

• 10+ years in quantitative research or related roles at buy-side/asset manager
• Strong Python skills for research, data pulls, back testing, and risk metrics
• Solid foundation in operations research, statistics, or quantitative finance
• Experience with SMAs or systematic investment strategies at scale
• Ability to collaborate with technical product and engineering teams
• Clear communicator of quantitative concepts to non-technical stakeholders

Responsibilities

• Design, research, and build derivatives-based overlays for equity and fixed income
• Backtest options overlays with realistic costs across SMA accounts
• Monitor risk metrics, Greeks, and portfolio exposures
• Create research code, data pipelines, and analytics for strategy design
• Translate research into scalable strategy specifications and playbooks
• Collaborate with PMs, product managers, and engineers to turn research into platform features
• Support daily P&L and risk monitoring

Skills

Python

Quantitative analysis

Derivatives knowledge

SMA strategies

Communication

Education

Mathematics/Statistics/Quantitative finance

Job description

Farther is a rapidly growing RIA blending traditional wealth management with fintech and cutting-edge technology. We are expanding our asset management team to build quantitative overlays and research-driven investment capabilities using Python.

As part of the team you’ll design, backtest, and implement options-based overlays across equity and fixed income, working closely with PMs and engineers to scale research into production-ready platforms with robust risk controls.