Role Description
Farther's asset management team (FAM) manages a growing suite of systematic investment strategies β 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 β covered calls, collars, protective puts β 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.
Your Impact
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Research, prototype, and back test options overlay strategies in Python β covered calls, cash-secured puts, collars, and protective overlays β with realistic assumptions for transaction costs, liquidity, and taxes across SMA accounts.
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Support PMs across equity and fixed income verticals by designing and applying derivatives-based overlays suited to each asset class.
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Monitor portfolio-level Greeks, exposures, and risk/return outcomes across many smaller accounts within rules-based risk parameters.
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Build and maintain research code, data pipelines, and analytics supporting systematic strategy design β signal construction, parameter sweeps, scenario and regime analysis.
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Translate research into clear, rules-based strategy specifications and playbooks that can be implemented consistently at scale.
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Evaluate new overlay ideas (income generation, hedging, outcome-oriented strategies) and communicate trade-offs clearly to internal stakeholders.
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Partner with product managers and engineers to convert manual workflows and research into scalable platform capabilities β strategy engines, trade generation, risk dashboards, monitoring tools.
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Support daily P&L, risk, and performance monitoring β including exception handling for unusual portfolio events.
Qualifications
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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.
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Solid Python skills for research and analytics β data pulls, optimization, back testing, risk metrics, and clean, maintainable codebases.
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Strong mathematical foundation: operations research, statistics, or quantitative finance background.
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Experience working with SMAs or systematic investment strategies at scale β understanding of multi-account implementation, portfolio construction, and associated operational complexity.
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Comfortable collaborating with technical product and engineering teams and thinking in terms of systems and workflows.
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Curious, self-directed, and comfortable operating in lean environments β you figure things out and don't wait to be told what to do.
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Clear communicator who can explain quantitative concepts to non-technical stakeholders (advisors, product, operations, leadership).
Bonus Points
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Familiarity with options, Greeks, volatility surfaces, or derivatives-based strategies β even if not from a live trading context.
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Experience specifically with fixed income or equity SMAs β multi-account implementation, tax-aware trading, lot-level considerations.
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Prior exposure to portfolio management, risk, or trading platforms (OEMS, risk systems, SMA overlay engines).
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Experience at a fintech or RIA where technology and investment management intersect.
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Familiarity with custodian or brokerage platforms used by advisors (e.g., Schwab, Fidelity).
Benefits
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Competitive comp package that rewards impact.
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Work alongside some of the brightest minds in fintech.
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Ground-floor opportunity at a fast-scaling startup.
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Chart your own growth path as we expand.
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Full health benefits + 401(k) matching & Roth IRA options.
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Unlimited PTO.