Top Hybrid Data & Analytics Jobs in Boston, MA

Leads complex data engineering initiatives for global cybersecurity analytics. Designs data architectures, ingestion pipelines, governance standards, and quality processes; collects and transforms large datasets; develops Power BI visualizations; improves data reliability and accessibility; documents systems; advises stakeholders; mentors team members; and responsibly applies AI tools to improve workflows while protecting confidential data.

Leads reporting, analytics, and optimization across Pfizer’s promotional content delivery ecosystem. Builds and maintains dashboards and report catalogs using Power BI and Adobe platforms, monitors adoption and usage trends, interprets metrics, and delivers actionable recommendations. Manages complex cross-functional projects involving Biopharma Operations, marketing, agencies, and stakeholders. Supports improved content effectiveness, speed to market, service efficiency, and cost optimization while leveraging AI-enabled insights and operating independently in a matrixed environment.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Lead and grow WHOOP’s Analytics Engineering team while owning the quality, scalability, and evolution of its analytics transformation layer. Build reliable, documented, tested data models; translate business and analytics needs into scalable solutions; and coordinate with Data Engineering and Analytics Platform on pipelines, contracts, and architecture. Establish dbt and software-engineering standards, manage team priorities and roadmap execution, and support AI-ready analytical data and development workflows.

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.

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.

Develop, implement, govern, and integrate enterprise ontologies and data models. Harmonize linked data, establish semantic and data-standardization guidelines, support knowledge organization and machine-learning integrations, and advocate semantic technology across Finance and Enterprise teams. Use W3C ontology standards and specialized tools to test, troubleshoot, and maintain models while collaborating with Technology, Product, and Machine Learning stakeholders.