State Street’s Financing Solutions organization needs to optimize financial resources across its core businesses (Agency Lending, Prime Services, Secured Financing/Repo) by developing quantitative models for pricing, balance sheet optimization, analytics, and risk management. The role will support decision-making across the franchise, particularly within Prime Services, by building and scaling analytics for pricing, balance sheet usage, and risk optimization.
Requirements
- Hands-on programming skills—Python (preferred) and comfort working with large datasets and performance‑sensitive code.
- Relational database fluency (e.g., Sybase, Oracle, SQL) and practical data engineering hygiene (schemas, indexing, query optimization).
- Experience analyzing, merging, and interrogating large datasets to uncover relationships and drive decisions
- Statistical modeling and backtesting experience (time series methods, classical statistics, validation, diagnostics).
- Experience with cloud computing (AWS, Databricks) for operationalizing models/workflows (containerization, orchestration, CI/CD for analytics).
- Undergraduate or Masters in Mathematics, Engineering, Computer Science, or related quantitative field; or equivalent practical track record.
- Strong market literacy across securities financing products (Agency Lending, Prime Brokerage—physical & synthetic, Repo/Secured Financing)
Responsibilities
- Develop quantitative models that optimize capital, liquidity, and balance sheet usage across the Prime Services (physical & synthetic) client base
- Incorporate capital, leverage, and liquidity considerations and translate model outputs into pricing frameworks and client/product profitability analytics.
- Build resource calculators and “what-if” tools (e.g., RWA/Liquidity actuals vs. forecasts) to support scenario planning, revenue forecasts, and allocation decisions.
- Design and maintain asset- and portfolio-level analytics and benchmarking methodologies reflecting market conditions, asset/client mix, and counterparty behavior.
- Construct dashboards and insights that provide timely, trusted views on key business metrics, including utilization, inventory, P&L/attribution, financing spreads, client/product ROC and pipeline.
- Source, normalize, and integrate market and peer data to identify opportunities/risks, and inform product strategy and client engagement.
- Define data requirements and work with Engineering/DA teams to build robust ETL/ELT processes, canonical data sets, and centralized metrics
Other
- Exceptional communication (written & verbal): able to explain complex models in accessible terms and influence senior stakeholders.
- A “do‑anything” owner’s mindset; creative, pragmatic, and willing to challenge current paradigms.
- 5+ years in financial services in quantitative/technical roles with measurable impact on pricing, resource optimization, or product profitability.
- Deep quantitative orientation with demonstrated experience in financial resource optimization (capital, liquidity, funding) and portfolio/pricing analytics within a front-office markets context.
- This role blends hands-on modeling and programming with product thinking, and rewards an entrepreneurial mindset that is comfortable with ambiguity, moves quickly from hypothesis to evidence, and communicates clearly to both business and technical audiences.
