Quantitative Researcher
A Tier 1 Investment Bank is seeking a Quantitative Researcher to join its Equity Derivatives business. This role sits directly on the trading desk and combines responsibilities across derivatives pricing model development, quantitative analytics, tool building, and front-office support. The ideal candidate will operate at the intersection of quant research, software engineering, and trader enablement-supporting both strategic development and day-to-day trading activity.
Key Responsibilities:
Develop, maintain, and enhance pricing and risk models for equity derivatives
Build and support trading tools for pricing, P&L attribution, hedging, and relative value analysis
Partner closely with traders, structurers, sales, and technology to deliver desk-aligned quant solutions
Own the full quant workflow: define the problem, research and implement a model, and deploy it to production
Calibrate and test models using market data, internal positions, and historical trading behaviour
Contribute to the strategic buildout of modelling libraries and analytics infrastructure
Provide first-line support for models used in daily trading and risk management
Assist in validation and documentation in line with model governance frameworks
Required Skills & Experience:
Postgraduate degree (MSc/PhD) in a quantitative subject such as Mathematics, Physics, Statistics, Computer Science, or Engineering
Strong understanding of derivatives pricing theory and numerical methods (stochastic calculus, PDEs, Monte Carlo, etc.)
Experience working in a front-office quant role, ideally with exposure to equity derivatives (vanilla or exotic)
Advanced programming skills in Python (required), with exposure to C++ or Java a strong plus
Prior experience working in production codebases, contributing to model libraries or analytics platforms
Comfortable translating trader requests into deliverable models or tools under real-time constraints
Familiarity with risk-neutral valuation, volatility surfaces, and calibration routines
Strong communication skills - able to work closely with trading and technology in a high-pressure environment
Preferred but not required:
Experience in model governance, documentation, or regulatory model validation
Familiarity with distributed computing, real-time analytics, or low-latency architecture
Background in product control, trade lifecycle, or intraday risk systems
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