Top Senior Data & Analytics Jobs in Boston, MA

Lead Data Scientist responsible for guiding projects, mentoring a team, developing data-driven solutions, and collaborating across departments to drive insights.

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

Lead and scale a casino analytics team to set analytics vision, drive experimentation strategy, and deliver executive-level insights. Partner with Revenue Operations, Data Science, and Product to build reporting, monitoring, and analytical frameworks that surface trends, risks, and growth opportunities. Coach leaders and analysts, align analytical roadmaps with business objectives, and foster analytical excellence and accountability.

As a Lead Data Engineer, you will collaborate in Agile teams to design and implement financial data solutions, utilizing extensive programming and cloud technologies.

Lead data and software QA for enterprise data platforms: define testing strategy, build automated test frameworks, validate ETL/ELT and data transformations, run data quality checks and reconciliations, test APIs and data products, analyze datasets with SQL to find defects, drive root-cause resolution, participate in Agile ceremonies, and mentor team members to improve quality practices.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal measurement, test-and-learn designs, elasticity and incrementality analyses, and deliver executive-ready recommendations to optimize revenue, margin, and share.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.