Quantitative Analytics Platform Manager

U.S. Bank • Charlotte, NC

5d • $143,905 - $169,300

About The Position

The role is responsible for supporting the delivery, governance, integration, and controlled production use of a proprietary analytics platform across approved business and technology workflows. This includes interface management, release coordination, regression testing, performance monitoring, production support, EUCT productionalization, documentation, entitlements, and controlled consumption through Excel, Python, Java, databases, APIs, and enterprise applications. The role works closely with quantitative development, technology, risk, and business users. Quantitative teams own the analytical methodology and core modeling logic; this role helps ensure those capabilities are made available through stable, supportable, reusable, and well-controlled production channels. The purpose of the role is to help establish consistent operating standards around the use of proprietary analytical capabilities, reducing reliance on locally managed tools, spreadsheets, prototypes, and one-off integrations.

Requirements

• 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.

Nice To Haves

• Experience supporting proprietary analytics platforms, pricing services, valuation frameworks, risk engines, market data environments, or quantitative applications.
• Familiarity with quantitative model development workflows, model lifecycle processes, production release controls, and controlled model consumption.
• Working familiarity with C++, Python, SQL, Java, Excel integration frameworks, APIs, databases, or front-office analytical tooling.
• Experience productionalizing end-user computing tools, including Excel-based applications used for pricing, valuation, risk, reporting, or recurring business processes.
• Experience implementing regression testing, automated testing, release certification, production monitoring, defect management, or rollback procedures.
• Knowledge of fixed income, derivatives, market data, curve construction, risk measurement, valuation, portfolio analytics, or P&L attribution.
• Experience designing or supporting controlled interfaces between analytical libraries, databases, business tools, applications, reporting environments, or workflow automation tools.
• Experience using AI-assisted tooling to improve software delivery, testing, documentation, support workflows, exception detection, operational monitoring, or knowledge management.
• Familiarity with governance, auditability, entitlement, explainability, and control considerations for AI-enabled tools in regulated environments.

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.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Senior