Quantitative Developer

Backend Python / Quant Developer – Fixed Income & Capital Markets Senior Backend Python / Quant Developer New York City $60-$85/hour 18 Month W2 Contract Experience: 7+ years Industry: Capital Markets / Investment Banking Position Summary We are seeking a Senior Backend Python / Quant Developer with strong experience in Fixed Income, Capital Markets, trading systems, and quantitative financial modeling . The ideal candidate will combine deep Python development skills with strong financial markets knowledge and experience building scalable, high-performance applications used by traders, risk teams, and quantitative analysts. This role requires someone who can work across backend engineering, quantitative analytics, financial models, market data, and trading workflows , partnering closely with Front Office, Quant, Risk, and Technology teams. Key Responsibilities Design, develop, and maintain high-performance backend applications and services using Python . Build quantitative and financial applications supporting Fixed Income trading, pricing, risk, valuation, and portfolio analytics . Develop and implement financial models, pricing methodologies, quantitative algorithms, and analytical tools . Work closely with traders, quantitative researchers, risk managers, and Front Office stakeholders to translate financial requirements into production-quality technology. Develop APIs, microservices, data pipelines, and backend services supporting trading and financial analytics platforms. Work with large volumes of market data, trade data, reference data, pricing data, and risk data . Implement and optimize models for areas such as: Fixed Income pricing and valuation Yield curves and interest-rate modeling Bond analytics P&L and risk analytics Sensitivities/Greeks Scenario and stress testing VaR and market risk Develop tools supporting the trade lifecycle , including trade capture, validation, enrichment, pricing, risk, and downstream reporting. Optimize Python applications and quantitative models for performance, scalability, and reliability . Integrate backend applications with databases, market-data systems, trading platforms, and enterprise APIs. Develop automated testing and validation frameworks for financial models and trading applications. Participate in architecture discussions and contribute to modernization of legacy trading and quantitative platforms. Troubleshoot production issues and work closely with technology and business teams to resolve issues impacting trading and risk workflows. Required Qualifications 7+ years of professional software development experience , with significant hands-on Python development. Strong object-oriented Python programming and experience developing production-grade backend applications. Strong understanding of Fixed Income and Capital Markets . Hands-on experience supporting trading, pricing, risk, or quantitative finance applications . Strong understanding of financial instruments such as: Bonds Treasuries Interest-rate products Swaps Experience with financial modeling and quantitative analytics . Strong understanding of concepts such as pricing, valuation, yield curves, discounting, risk measures, P&L, and sensitivities . Experience working directly with Front Office, Trading, Quant, Market Risk, or Portfolio Management teams. Strong SQL and relational database experience. Experience building REST APIs, backend services, or microservices . Strong analytical and problem-solving skills. Preferred Qualifications Experience with NumPy, Pandas, SciPy, Statsmodels, scikit-learn , or similar quantitative Python libraries. Experience with C++ , Java, or another backend programming language. Experience with QuantLib or other financial modeling/pricing libraries. Knowledge of market data platforms and trading systems such as Bloomberg, Refinitiv, Murex, Calypso, Summit, or similar. Experience with Kafka or other event-driven technologies . Experience with cloud technologies such as AWS, Azure, or GCP . Experience with Docker/Kubernetes and CI/CD. Knowledge of market risk, VaR, stress testing, FRTB, XVA, CVA, or counterparty risk . Experience working in an investment bank or financial institution . Ideal Candidate The ideal candidate is not simply a Python developer . They should be a strong combination of: They should be comfortable discussing both technical implementation and financial concepts with traders, quants, risk managers, and technology teams. Strong candidates will have experience taking financial models or trading requirements and turning them into scalable, production-ready Python applications . #J-18808-Ljbffr Matlen Silver