Options Quant Researcher

BHFT

Mid-Senior Quant Researcher specializing in options at BHFT, a trading firm. Responsible for developing automated trading strategies with a focus on options and volatility.

Posted 7/1/2026full-timeRemote • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying fully automated options trading strategies, with a strong focus on risk-adjusted performance and robust signal research pipelines. Proficient in Python and quantitative analysis, with a solid understanding of options mathematics and market microstructure.

Highest-signal resume keywords

Python ProgrammingRelative Value Strategy DevelopmentAutomated Trading StrategiesOptions Mathematics KnowledgeQuantitative Research Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NumPyPandasMatplotlibSciPyFeature EngineeringBacktestingSignal ResearchOptimization LibrariesStatistical ArbitrageSpread Trading

Soft Skills

Clean Code PracticesReproducible ExperimentsVersion Control

Tools & Technologies

QuantLibIn-House Libraries

Industry Keywords

Options TradingMarket MicrostructureRisk-Adjusted PerformanceMid-Frequency TradingExecution Artifacts

Tech Stack

Tools & technologies

NumpyPandasPython

About the role

Key responsibilities & impact

Own end-to-end options strategy research: hypothesis → data → modeling → backtesting → production → live monitoring and iteration
Work on Relative Value, Statistical Arbitrage, and Spread Trading strategies specific to the options universe (the stack above)
Build and own the volatility fitter the signals sit on – calibrating arbitrage-free, temporally stable surfaces (SVI/SSVI or a proposed alternative) on realistic data (wide bid/ask, missing strikes, gaps, latency), with attention to residual noise near expiry / illiquid strikes / events
Translate strategy output into execution – routing a target delta-order across option legs to minimize Greek risk, with inventory-aware quoting that shifts price/size against live vega/gamma/skew, and awareness of options microstructure (spreads, queue, adverse selection, latency)
Build and maintain mid-frequency (MFT), fully automated strategies with a strong live-performance focus
Track record of deploying fully automated strategies with Sharpe > 2 (or demonstrable equivalent risk-adjusted performance)
Design robust signal research pipelines (feature engineering, labeling, validation, regime analysis)
Develop realistic backtests and live-simulation frameworks accounting for slippage, spreads, latency, partial fills, and market impact
Work in tight feedback loops with trading and execution to improve PnL, robustness, and risk-adjusted performance
Debug and tune research outputs under live conditions: data issues, execution artifacts, microstructure noise, and changing market regimes

Requirements

What you’ll need

Python (mandatory), strong use of NumPy, pandas, matplotlib, SciPy, and optimization/ML libraries
Strong research engineering: clean code, reproducible experiments, versioning, and production readiness
Hands-on experience developing Relative Value strategies
Experience building systematic strategies in equities / futures / options / other listed derivatives (any strong TradFi systematic experience is relevant)
Good knowledge of option maths and strong options intuition
Familiarity with common quant tooling (e.g., QuantLib and/or in-house libraries)

Benefits

Comp & perks

Experience a modern international technology company without the burden of bureaucracy.
Enjoy excellent opportunities for professional growth and self-realization.
Work remotely from anywhere in the world with a flexible schedule.
Receive compensation for health insurance, sports activities, and non-professional training.