Top Senior Data & Analytics Jobs

The Senior Analytics Engineer will build and optimize data infrastructure to drive data-driven decision-making, creating actionable insights for therapy and business teams.

As a Senior Data Scientist, you will drive product analytics and experimentation, develop metrics, and collaborate with cross-functional teams to inform strategic decisions.

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.

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.

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.