Top Data & Analytics Jobs in Boston, MA

Analyzes business performance, trends, competitor filings, and product-line data for personal lines property and specialty insurance. Develops advanced queries and analytical tools, conducts state and countrywide reviews, manages projects and workstreams, and recommends strategic and tactical improvements to products, pricing, technology, and business initiatives. Presents findings to product managers and serves as a subject matter expert on assigned states and products.

Conduct exploratory and hypothesis-driven analysis across disparate data sources to identify business opportunities, risks, and causal relationships. Build metrics, reports, and dashboards to monitor performance and experiments, while partnering with decision-makers to communicate insights and improve data-driven decisions. Contribute to data structure modernization, modeling, and ETL initiatives while managing multiple analytical projects.

As a Decision Analytics Associate Consultant, you will develop statistical models, apply analytic techniques, and communicate results to clients. You will also design custom analyses and guide team projects while mentoring Associates and maintaining client relationships.

Supports PwC Deals diligence analytics projects through data gathering, analysis, research, visualization, data mining, algorithm development, and preparation of reports and presentations. The intern will use Alteryx and Power BI, integrate data from multiple sources, develop data-driven insights for clients, and learn from advisory professionals while contributing to cloud, data architecture, and AI-related initiatives.

Supports retail space planning through data analytics, performance reporting, and store layout optimization. Creates and validates Power BI dashboards and reporting tools, analyzes space productivity, maps data, and identifies actionable opportunities. Collaborates with Space Planning and Commercial Solutions teams while maintaining merchandising standards. The co-op combines business analytics, retail strategy, database concepts, data visualization, and emerging AI tools in a hybrid environment.

Build and operate production data pipelines supporting analytics, AI, and agentic workflows. Responsibilities include implementing canonical data models, maintaining Databricks or Snowflake platforms, monitoring reliability, responding to incidents, validating healthcare data mappings, improving performance and cost, and documenting architecture. Requires strong SQL and Python skills, cloud data platform experience, ETL/ELT orchestration expertise, and healthcare or pharmaceutical data experience.

Leads a team of analytics professionals and owns client and product analytics strategy, dashboards, reporting, metrics governance, and self-service capabilities. Partners with Product, Engineering, Client Success, and account teams to define trustworthy KPIs, improve data quality, translate complex data into actionable insights, and prioritize analytics initiatives. The role combines people leadership with hands-on BI solution design and supports client-facing analytics offerings.

Conduct quantitative and qualitative research, including data cleaning, statistical analysis, subgroup comparisons, regression, clustering, and significance testing. Manage online research communities for teens, parents, and counselors, overseeing recruitment, engagement, incentives, research programming, and member experience. Translate findings into dashboards, visualizations, reports, and presentations for nontechnical audiences. Collaborate cross-functionally to shape research agendas, deliver rapid insights, and advance data-driven initiatives.

Leads WHOOP’s data governance function, defining strategy, operating models, ownership, data contracts, event taxonomy, cataloging, access policies, quality standards, and privacy compliance. Builds and coaches a senior team while partnering across engineering, analytics, product, legal, GRC, and InfoSec. Establishes governance frameworks, automated quality monitoring, access controls, compliance practices, and metrics, while embedding standards into technical workflows and advancing AI-powered governance.

Own end-to-end data products, including source onboarding, API and file-feed ingestion, orchestration, incremental and idempotent pipelines, Snowflake and dbt Cloud modeling, testing, documentation, alerting, and production reliability. Establish engineering standards, manage secrets and governance, use AI coding tools responsibly, collaborate with vendors and stakeholders, and mentor junior engineers.