Top Senior Data & Analytics Jobs

Lead Harvard's data governance program: convene executive and steward groups, develop enterprise data strategy, set policies/standards, improve metadata and data quality, ensure privacy/compliance, measure governance effectiveness, and drive change across the university.

The Manager of Portfolio Forecasting leads carrier portfolio premium forecasting, collaborates on strategy, analyzes performance, and mentors analysts.

Responsible for data analysis and modeling to optimize pricing strategies, support business decision making, and mentor junior team members.

Manage catastrophe portfolios using advanced statistical modeling and analytics. Develop solutions to optimize risk profiles and create impactful visuals for decision-making.

Lead and manage a data engineering team to design, build, and optimize scalable ETL/ELT pipelines, migrate legacy systems to cloud-native platforms, enforce data quality and security, define SLAs, and support analytics and operational data needs within a regulated banking environment.

Lead end-to-end credit risk analytics to inform underwriting, pricing, and product strategy. Build forecasting, unit-economics, and loss‑forecast models; design and analyze live tests; develop and implement credit policy; partner with cross-functional teams and external partners; apply AI-assisted analytics; and automate credit decisioning to balance growth with portfolio health.

As a Quantitative Product Specialist, you'll engage clients with QIS tools, enhance product adoption, contribute to marketing strategies, and provide data-driven insights to improve investment decisions.

The Sr. Business Systems Analyst will gather business requirements for CDP and MAP, collaborate with teams to prioritize technology needs, and create documentation for business processes and training.

The Business Analyst will facilitate operational excellence by analyzing product requirements, managing workflows in business systems, and ensuring timely software delivery through collaboration and improvement of processes.

Develop and maintain complex datasets for assumption setting, valuation, projections, and analysis. Lead data quality controls, drive data improvements, collaborate with cross-functional teams, perform programming-based analysis (SQL/Python/R/SAS), review code/logic, and manage data-related projects to support actuarial models and business decisions.

Works with business partners to gather and translate B2B requirements into system and interface specifications. Analyzes functional and data needs, documents EDI/SAP/XML mappings, facilitates cross-functional meetings, coordinates trading partners, and supports B2B project lifecycle and system enhancements.