Vice President, Data Management & Quantitative Analysis- Quant Developer

Vice President, Data Management & Quantitative Analysis- Quant Developer At BNY, our culture empowers you to grow and succeed. As a leading global financial services company at the center of the world’s financial system we touch nearly 20% of the world’s investible assets. Every day around the globe, our 50,000+ employees bring the power of their perspective to the table to create solutions with our clients that benefit businesses, communities and people everywhere. We continue to be a leader in the industry, awarded as a top home for innovators and for creating an inclusive workplace. Through our unique ideas and talents, together we help make money work for the world. This is what #LifeAtBNY is all about. We’re seeking a future team member for the role of Vice President, Data Management & Quantitative Analysis- Quant Developer to join our Margin Methodology Development and Backtesting team. This role is located in Pune and will be working in a hybrid capacity. (Currently 4 days a week in the office). In this role, you’ll make an impact in the following ways: We are seeking a Quant Developer with strong experience in margin methodology development, backtesting, and model validation support , with primary focus on Securities Finance businesses , including Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions . This role will focus on building and enhancing analytics and tooling to support the design, implementation, backtesting, review, and approval of margin methodologies across these businesses. The ideal candidate will have experience in Historical VaR , stress testing , and dynamic margin frameworks , including Rules-Based Dynamic Margin and Stress-Based Dynamic Margin methodologies. The successful candidate will combine strong quantitative modeling expertise , hands-on Python/C++ development capability , and practical understanding of margining use cases relevant to financing, collateralized products, and client risk management . Develop, maintain, and support Python/C++ quantitative libraries and analytical tools for margin methodology development , backtesting , and stress testing across Securities Finance businesses , including Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions . Design and implement robust backtesting frameworks for margin models using historical simulation , Historical VaR , and stress-based techniques . Support the development, enhancement, and performance assessment of Rules-Based Dynamic Margin and Stress-Based Dynamic Margin methodologies. Perform quantitative analysis on margin model outcomes, including coverage testing , procyclicality assessment , sensitivity analysis , and ongoing model performance monitoring . Analyze historical market data and stress periods to assess margin model behavior under both normal and stressed market environments relevant to financing and collateralized trading businesses . Work closely with quantitative analytics, risk, model governance, business stakeholders, and technology teams to support the model review, validation, and approval process . Prepare quantitative evidence, documentation, and supporting analytics for internal governance , model oversight, and regulatory or control reviews. Investigate issues related to market data, scenario generation, backtesting exceptions, and margin model performance. Partner with platform engineering and technology teams to integrate margin analytics and backtesting tools into enterprise risk and margin systems. Contribute to AI-enabled quantitative workflow solutions where relevant for analytics, monitoring, controls, and reporting. To be successful in this role, we’re seeking the following: Bachelor’s or Master’s degree in a relevant technical discipline such as Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or another quantitative field . Strong programming skills in Python and/or C++ , with proven experience building quantitative analytics libraries, risk tools, or backtesting engines. Strong understanding of margin methodologies , model backtesting , Historical VaR , and stress testing techniques . Experience with Rules-Based Dynamic Margin and/or Stress-Based Dynamic Margin methodology development, calibration, backtesting, or performance assessment. Good understanding of margining concepts relevant to Securities Finance , including businesses such as Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions . Familiarity with model governance , validation expectations , and approval processes for quantitative methodologies. Strong knowledge of market risk concepts , including VaR , stress testing , scenario analysis , sensitivities , and tail-risk evaluation . Experience working with historical market data , scenario construction, and quantitative model performance analysis. Strong analytical and problem-solving skills with the ability to interpret model behavior and communicate findings effectively. Good understanding of software engineering principles, including object-oriented design , testing, code quality, and maintainable development practices. Strong communication and collaboration skills, with the ability to work across quantitative, business, risk, governance, and engineering teams. Preferred Qualifications Experience supporting margin methodologies in Securities Finance businesses, especially Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions . Experience in securities financing, clearing, exchange, CCP, derivatives margin, counterparty risk, or market risk environments. Exposure to margin model validation , regulatory review , or quantitative model governance processes. Knowledge of fixed income, equities, FX, and financing products , particularly from a risk, collateral, and margining perspective . Familiarity with procyclicality controls , margin coverage standards , and stress calibration practices . Experience in quantitative development, model development, or risk analytics roles within investment banks, clearing houses, exchanges, broker-dealers, or other financial market infrastructure institutions . Ideal Candidate Profile Hands-on Quant Developer with strong experience in risk and margin analytics Deep interest in margin methodologies for Securities Finance businesses Proven capability in backtesting quantitative methodologies using historical market data Comfortable operating in environments involving model governance, validation, and approval Able to bridge quantitative research , model implementation , and production-grade analytics tooling Experience supporting dynamic margin frameworks for Prime Services, Repo, Securities Lending, Clearing, or Wealth Solutions is highly desirable At BNY, our culture speaks for itself, check out the latest BNY news at: BNY Newsroom BNY LinkedIn Here’s a few of our recent awards: America’s Most Innovative Companies, Fortune, 2025 World’s Most Admired Companies, Fortune 2025 “Most Just Companies”, Just Capital and CNBC, 2025 Our Benefits and Rewards: BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter. BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.