Quantitative Analytics Platform Manager

Responsibilities

• Own the operating model for approved analytics platform access across Excel, Python, Java, databases, APIs, and related application layers.
• Define and maintain standards for access patterns, version control, entitlements, testing, documentation, support procedures, and production evidence.
• Partner with quantitative developers and technology teams to deliver stable, reusable, performant, and controlled analytics interfaces.
• Support release management and regression testing for analytics platform changes, including API updates, calculation changes, interface changes, downstream impacts, defect review, certification, and rollback planning.
• Lead productionalization of high-value or high-risk Excel-based analytical tools, including standardized inputs, outputs, data sourcing, calculation sequencing, ownership, documentation, and controls.
• Support performance monitoring and remediation across Excel, Python, Java, database, batch, and application-based workflows.
• Help define database interaction patterns for market data retrieval, reference data, static data, output persistence, audit trails, usage monitoring, and downstream consumption.
• Support controls around curve creation, curve storage, curve publishing, overrides, version references, restricted data, and controlled database-consumed outputs.
• Use AI-assisted tooling where appropriate to improve documentation, test-case generation, regression analysis, exception detection, support workflows, and platform knowledge management.
• Serve as a coordination point across quantitative model owners, technology partners, business users, risk stakeholders, and support teams.

• Bachelor’s degree in Computer Science, Mathematics, Engineering, Physics, Quantitative Finance, or a related quantitative or technical discipline.
• 7+ years of experience in front-office technology, quantitative platforms, analytics infrastructure, risk systems, market data platforms, trading systems, or related financial technology environments.
• Experience supporting analytical, pricing, risk, valuation, market data, reporting, or trading-related systems in a regulated financial services environment.
• Strong understanding of software development lifecycle, release management, regression testing, change control, production support, and operational controls.
• Experience delivering analytical capabilities through Excel, Python, Java, databases, APIs, services, or enterprise applications.
• Experience working with production controls, entitlements, documentation, auditability, evidence retention, and operational risk processes.
• Working knowledge of modern software architecture, API design, database technologies, integration patterns, and performance monitoring.
• Strong communication skills with the ability to work across quantitative, technology, business, risk, and control teams.

Demonstrates expertise in managing analytics platforms, including access control, version management, and performance monitoring. Proficient in delivering analytical capabilities using Excel, Python, Java, and databases within regulated financial environments.