Top Quant Finance Jobs in NYC, NY

Lead quantitative model risk reviews for Treasury models used in resolution, recovery, liquidity, stress testing and budgeting. Assess conceptual soundness, design benchmarks and performance metrics, guide model usage, liaise with developers/users/compliance, and evaluate model performance regularly. Provide technical write-ups and escalate material issues.

Develop and evaluate derivatives pricing models across equity and fixed income products; conduct alpha research, relative value analysis, backtesting, and signal implementation; build real-time P&L, risk, and analytics tools; assess model limitations; and advise portfolio managers and risk teams on practical model usage and business impact.

Conduct quantitative research for systematic securitized-credit trading strategies, focusing on agency MBS and CMOs. Responsibilities include developing trading signals, prepayment models, pricing and hedging analytics, researching new markets, improving systematic trading infrastructure, and supporting portfolio managers. The role requires applied statistics, programming, financial markets expertise, and communication skills, with AI tools used to improve research and trading workflows.

Analyze and manage Consumer & Community Banking interest rate risk and transfer pricing across deposits, cards, mortgages and loans. Maintain IRR models, perform scenario and sensitivity analysis, refine FTP methodologies, produce reports, and communicate recommendations to senior stakeholders. Leverage Python and statistical techniques, collaborate across teams, and support governance and regulatory requirements.

Lead model risk reviews for complex credit, interest rate, and equity pricing models. Assess model design, validation, performance metrics, and governance; develop benchmarks; guide model remediation; act as business liaison; and manage and mentor junior team members.

Supports portfolio managers and the CIO in evaluating, selecting, monitoring, and negotiating investments with external hedge funds, including quantitative and CTA strategies. Conducts manager research, develops investment assessment and return forecasting frameworks, and makes evidence-based hiring or divestment recommendations. Also supports internal macro trading research by optimizing quantitative strategies and managing automated analytics. The role requires strong quantitative investment expertise, communication skills, decisiveness, and interest in owning investment decisions.

Develop and implement quantitative models, risk analytics, hedging tools, portfolio valuation solutions, and optimization capabilities for capital markets risk platforms. Integrate models into production systems with engineering teams, modernize risk technology architecture, validate methodologies, improve performance, and support analytics across multiple asset classes while collaborating with Risk, Technology, and Front Office stakeholders.

Make markets and manage risk across sports and financial prediction contracts. Develop real-time pricing models, integrate them into production trading systems, monitor and improve model performance, identify market-taking opportunities, and implement automated trading strategies. Collaborate with product, engineering, quant, and compliance teams to launch new markets and contract types. Flexible working hours are required to align with global sporting schedules.

The Risk Analyst role requires conducting operational risk, credit risk, market risk analysis, creating models, and developing analytics with a quantitative background.

The role involves developing pricing and risk analysis tools, working closely with the trading desk, and addressing complex financial inquiries.

The Quant will optimize trading strategies, research and test potential alphas, and enhance the production trading system within a collaborative team.

Join the Equity Derivatives team to develop pricing models, conduct quantitative research, build Python/SQL tools, design and run backtests, support traders on risk and trade analysis, and integrate models with trading and risk infrastructure using statistical and ML techniques.

Review and evaluate quantitative finance tasks for technical accuracy and real-world realism. Identify missing assumptions, unrealistic constraints, edge cases, and data or backtesting issues. Provide concise, structured written feedback and actionable recommendations. Collaborate with other experts to calibrate evaluations and maintain consistent quality standards throughout a high-engagement, remote contractor sprint.

Design and implement quantitative risk models and real-time monitoring for perpetuals and commodity derivatives. Build stress testing, default and guarantee-fund frameworks, translate model outputs into exchange policy (margin, liquidation, limits), and ensure CFTC reporting and capital compliance. Partner with engineers to deploy production-quality risk systems and prioritize risk architecture improvements as trading and exposure evolve.

Design, validate, and refine quantitative methodologies for direct indexing, portfolio construction, tax-loss harvesting, and tracking-error minimization. Build backtests, analyze large financial datasets (market, execution, tax lots), improve optimization formulations, and collaborate with engineering and product teams to productionize robust, risk-aware investment models.

Support senior researchers to develop, implement, validate, and maintain option pricing models and quantitative analytics. Conduct statistical analysis on large financial datasets, contribute to new products and tools, document findings, and communicate technical results to technical and non-technical stakeholders in a hybrid NYC environment.

Lead development of advanced equity derivatives risk analytics (volatility surface calibration, vanilla and exotic option pricing, VaR, stress testing). Partner with trading, risk, and quant teams to architect scalable pricing and risk engines, advise senior stakeholders on exposures and model assumptions, and drive methodological innovation for complex equity structures.

Join MerQube's New York team to model, backtest, and launch indices and options-based strategies. Develop implied volatility and pricing frameworks for options and exotic derivatives, translate models into production-ready Python indices, collaborate with financial engineering and clients, use datasets like FactSet and LSEG Refinitiv, and contribute to thought leadership.