Portfolio Manager, Quantitative

Farther is a rapidly growing RIA that combines expert advisors with cutting-edge technology - delivering a comprehensive, tailored wealth management experience.

Farther’s founders are leaders and innovators from the private wealth industry who possess a unique blend of traditional wealth management, fintech, and technology production expertise. We’re backed by top-tier venture capital firms, fintech investors, and industry leaders.

Joining Farther means joining a collaborative team of entrepreneurs who are passionate about helping their clients and our teammates achieve more. If you’re the type who breaks through walls to get things done the right way, we want to build the future of wealth management with you.

Farther's asset management team (FAM) manages a growing suite of systematic investment strategies — and we're expanding into options-based overlays. We're looking for a quantitatively-minded Investment Associate who can help design, research, and build out this capability from the ground up.

This isn't a seat where you'll be handed a mandate and left to trade. You'll work closely with experienced PMs across equity and fixed income to apply derivatives-based overlays across those strategies — covered calls, collars, protective puts — and use Python to research and systematize everything you build. Over time, you'll be a key voice in translating that work into a scalable platform alongside our product and engineering teams.

• Research, prototype, and back test options overlay strategies in Python — covered calls, cash-secured puts, collars, and protective overlays — with realistic assumptions for transaction costs, liquidity, and taxes across SMA accounts
• Support PMs across equity and fixed income verticals by designing and applying derivatives-based overlays suited to each asset class
• Monitor portfolio-level Greeks, exposures, and risk/return outcomes across many smaller accounts within rules-based risk parameters
• Build and maintain research code, data pipelines, and analytics supporting systematic strategy design — signal construction, parameter sweeps, scenario and regime analysis
• Translate research into clear, rules-based strategy specifications and playbooks that can be implemented consistently at scale
• Evaluate new overlay ideas (income generation, hedging, outcome-oriented strategies) and communicate trade-offs clearly to internal stakeholders
• Partner with product managers and engineers to convert manual workflows and research into scalable platform capabilities — strategy engines, trade generation, risk dashboards, monitoring tools
• Support daily P&L, risk, and performance monitoring — including exception handling for unusual portfolio events

• 10+ years of experience in quantitative research, investment analytics, systematic strategies, or a closely related role at a buy-side firm, asset manager, fintech, or financial services company
• Solid Python skills for research and analytics — data pulls, optimization, back testing, risk metrics, and clean, maintainable codebases
• Strong mathematical foundation: operations research, statistics, or quantitative finance background
• Experience working with SMAs or systematic investment strategies at scale — understanding of multi-account implementation, portfolio construction, and associated operational complexity
• Comfortable collaborating with technical product and engineering teams and thinking in terms of systems and workflows
• Curious, self-directed, and comfortable operating in lean environments — you figure things out and don't wait to be told what to do
• Clear communicator who can explain quantitative concepts to non-technical stakeholders (advisors, product, operations, leadership)

• Familiarity with options, Greeks, volatility surfaces, or derivatives-based strategies — even if not from a live trading context
• Experience specifically with fixed income or equity SMAs — multi-account implementation, tax-aware trading, lot-level considerations
• Prior exposure to portfolio management, risk, or trading platforms (OEMS, risk systems, SMA overlay engines)
• Experience at a fintech or RIA where technology and investment management intersect
• Familiarity with custodian or brokerage platforms used by advisors (e.g., Schwab, Fidelity)