Top Data & Analytics Jobs in Boston, MA

As a Lead Data Engineer, you will collaborate with Agile teams, develop technical solutions, and enhance cloud-based data warehousing to empower financial services for customers.

The Associate Principal will translate client needs into analytical specifications, ensure quality control of analytical outputs, and deliver clear insights while overseeing methodologies and clinical context research.

The Applied AI & Analytics Associate will conduct high-impact analytical work across functions, utilizing AI and data to drive business decisions and improvements, while collaborating with senior stakeholders and building analytical tools and models.

Lead the strategy and execution of real-world data capabilities, focusing on data lifecycle management, vendor relationships, and collaboration with various teams to deliver analysis-ready datasets.

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 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.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

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.