Top Data & Analytics Jobs in Boston, MA

Leads the design, development, and ownership of scalable data systems, ELT pipelines, data models, and Snowflake architectures supporting analytics, experimentation, machine learning, and business decisions. Partners cross-functionally to deliver reliable, governed data solutions; improves quality, observability, testing, documentation, and operational practices; mentors engineers; and shapes technical direction through automation, technology evaluation, and AI-enabled engineering.

Build and own trusted data products, dimensional models, semantic layers, and dbt transformations that support analytics, experimentation, machine learning, reporting, and decision-making. Partner with cross-functional teams to translate business needs into scalable datasets, improve data quality and governance, establish engineering standards, and drive self-service analytics. Mentor engineers and analysts while leveraging AI tools to improve development, documentation, and quality.

Analyze brand marketing performance across channels, audiences, creative, and markets. Design and evaluate incrementality tests, brand lift studies, geo-lift experiments, and marketing mix models. Build dashboards and reporting frameworks, synthesize survey, media, web, and brand health data, and provide recommendations that guide creative strategy, media planning, and investment decisions. Partner with Brand Marketing, Media, Data Science, and external measurement teams.

Leads product analytics across core product, hardware, and algorithms while managing and developing analysts. Partners with cross-functional teams to define KPIs, evaluate experiments, analyze member behavior and product performance, build scalable analytics processes, and influence product strategy through actionable insights. The role requires hands-on analysis, advanced SQL, data warehousing expertise, strong storytelling, and the ability to guide senior stakeholders and technical teams.

Analyze lifecycle marketing communications across channels, segments, and lifecycle stages to identify engagement, monetization, and retention insights. Partner with Lifecycle Marketing stakeholders, design and evaluate A/B tests, build dashboards and reports, develop data models, and present recommendations that improve targeting, timing, content, and member experience.

Leads WHOOP’s Analytics Engineering function by owning the analytics data model, semantic layer, data quality standards, and analytics platform strategy. Manages and develops a team of Analytics Engineers, partners with Data Platform Engineering, establishes development and governance practices, and drives cross-functional data initiatives. The role also communicates data architecture, strategy, and roadmap to senior leadership while evaluating modern analytics and AI-ready data technologies.

The Senior Business Analyst partners with Platform Engineering to measure the business impact of infrastructure, identity, authentication, and security initiatives. Responsibilities include analyzing conversion, engagement, retention, and purchase funnels; designing experiments; assessing security and member-experience tradeoffs; analyzing gross margin, COGS, and cloud hosting costs; building dashboards and reports; and presenting actionable insights to stakeholders and senior leadership.

Lead operational analytics for WHOOP’s global operations, identifying inefficiencies across shipping, fulfillment, inventory, costs, and service levels. Own metrics, forecasting, spend tracking, variance analysis, and cost-reduction initiatives while partnering with Operations, Finance, Membership Services, vendors, and Data Engineering. Build trusted data assets, pipelines, semantic-layer definitions, dashboards, and performance reviews. Manage and mentor analysts while influencing strategic prioritization and resource allocation through data-driven insights.

Design, build, and operate WHOOP’s data platform infrastructure, including lakehouse, warehouse, and streaming systems. Improve performance, reliability, cost efficiency, observability, and developer experience across AWS-based data systems. Develop internal tools, APIs, automation, CI/CD, and infrastructure-as-code practices. Partner with data, ML, analytics, and software engineering teams to support scalable workflows, governance, and production excellence while using AI-assisted development tools effectively.

Analyze growth marketing campaign performance, develop dashboards, translate media and conversion data into actionable insights, and support experimentation and measurement. Partner with marketers and Data Science to apply attribution, marketing mix modeling, and forecasts. Inform budget allocation, pacing, KPI definition, and growth planning while communicating recommendations to technical and non-technical stakeholders.