Top Data & Analytics Jobs in Boston, MA

Leads Customer Success analytics strategy, executive business reviews, customer experience and voice-of-customer insights, enablement impact measurement, and data foundation development. Manages two analysts, partners with data engineering and data science, applies statistical and experimental methods, analyzes structured and unstructured customer data, and uses AI tooling to improve self-service and recurring analytics. Translates ambiguous business questions into actionable recommendations for senior leaders.

Own high-impact revenue strategy analyses from problem framing through recommendations and decision support. Analyze marketplace performance, lead economics, monetization, retention, product adoption, and operating models using SQL, Python, financial modeling, and cross-functional data. Advise senior leaders, create executive- and board-ready materials, improve metric reliability, build reusable analytical frameworks, and influence decisions across Revenue, Product, Finance, and Operations.

The Data Scientist II will lead and execute health economic outcomes research projects, collaborate with stakeholders, and build analytical infrastructure while adhering to regulations.

Designs conceptual, logical, and physical data models for R&D research and clinical domains. Translates scientific and business requirements into reusable, scalable, AI-ready data structures that support analytics, machine learning, data integration, and standardized workflows. Partners with domain experts, data engineers, architects, data scientists, and governance teams to apply enterprise standards, schemas, ontologies, metadata, quality rules, and lineage. Promotes shared data assets and ensures models are implementable, interoperable, and aligned with evolving R&D needs.

Participate in a rotational analyst development program focused on using data and technology to analyze performance trends, identify business opportunities, and support insurance operations. Complete training, mentorship, and rotational assignments while developing strategic, technical, analytical, communication, and business skills. Use tools such as Excel, SQL, Python, R, SAS, Snowflake, Power BI, and emerging AI technologies to generate business insights.

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.

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.

The Analytics Manager investigates business questions, delivers actionable insights, maintains data models and Looker dashboards, and communicates findings through presentations and visualizations. The role develops testing frameworks, subscription unit-economic models, marketing attribution, retention and cohort forecasts, and customer segmentation. It also partners with Product and Engineering to improve application tracking and customer behavior visibility.

Own the design, governance, and evolution of the enterprise data lake and warehouse. Responsibilities include developing conceptual, logical, and physical data models; defining source-to-target mappings; reconciling legacy CRM and operational data; establishing data quality frameworks; administering schemas, views, access controls, and performance; and partnering with engineering and business stakeholders to support scalable, self-service analytics.

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.