State Street's Financing Solutions organization needs to optimize financial resources across its core businesses (Agency Lending, Prime Services, and Secured Financing/Repo) by developing and scaling analytics for pricing, balance sheet usage, and risk optimization. This involves designing models, data pipelines, and decision frameworks to inform capital and liquidity deployment, inventory and financing management, and client/product pricing.
Requirements
- Deep quantitative orientation with demonstrated experience in financial resource optimization (capital, liquidity, funding) and portfolio/pricing analytics within a front-office markets context.
- 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).
- 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.
- Undergraduate or Masters in Mathematics, Engineering, Computer Science, or related quantitative field; or equivalent practical track record.
- 5+ years in financial services in quantitative/technical roles with measurable impact on pricing, resource optimization, or product profitability.
- Partnering closely with Trading, Client Management, Technology, Operations, Risk, and Business Development.
