Top Data & Analytics Jobs in Boston, MA

Leads data transformation and governance for the Personal Lines Product, Pricing, and Underwriting domain. Develops data roadmaps, translates plans into epics, guides modernization onto a new technology stack, governs data policies and regulatory protections, and coordinates stakeholders across business and technical teams. The role requires strong insurance data expertise, knowledge of complex data models and warehousing, Agile collaboration, and experience with platforms such as Guidewire PolicyCenter.

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.

Leads the global social analytics function, managing four regional managers and establishing measurement standards across paid, organic, influencer, and earned channels. Builds the team and operating model while advancing AI-powered, agent-driven insight generation. Oversees social listening, trend and competitor detection, campaign and brand-impact measurement, and executive reporting. Partners with social, marketing, creative, media, product, brand, and regional teams to shape strategy and investment.

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.

Analyze and visualize large customer datasets, build production-grade data models and scalable data products, automate manual analytical workflows, and create AI-assisted, conversational, and self-service analytics experiences. Translate ambiguous stakeholder needs into actionable solutions while collaborating across teams and experimenting with generative AI and modern data technologies.

Design and execute advanced statistical and data analyses for client projects, using tools such as R, Tableau, SAS, VBA, and Excel. Translate data into actionable insights, communicate findings to clients and internal teams, collaborate on solution implementation, and take ownership of project deliverables.

Leads the Managed Services analytics roadmap, KPI governance, Power BI dashboard strategy, reporting automation, and AI-augmented metrics services on InterSystems IRIS. Provides technical leadership in SQL, ObjectScript, APIs, data models, interoperability, query optimization, and application performance. Establishes data-quality and reporting standards, develops predictive analytics, mentors analysts and engineers, investigates complex issues, and advises senior leadership on operational performance, risks, and investment priorities.

Designs, builds, administers, and supports cloud data architectures, databases, schemas, metadata repositories, ETL processes, and analytic models. Leads data quality, governance, troubleshooting, testing, automation, reporting, dashboards, and infrastructure design. Collaborates with Agile teams to translate business requirements into technical capabilities and supports decision-making for Audit and business management. The role is full-time onsite at an eligible Federal Reserve location and requires extensive security screening.

Supports client-facing diligence analytics projects by gathering, integrating, and analyzing data; developing data-driven insights; creating dashboards and reports; conducting research and data mining; contributing to algorithm development; and preparing presentations. The intern uses Alteryx and Power BI, collaborates with advisory teams, and gains exposure to cloud platforms, data architecture, data science, and AI applications.

Leads the data engineering team, including hiring, coaching, technical direction, platform architecture, data pipelines, Snowflake warehousing, governance, quality, observability, and incident support. Partners with Data Science, Analytics, Clinical Operations, Biostatistics, and Business Development to deliver trusted data products for clinical operations, asset evaluation, reporting, and machine learning. Oversees budgeting, resourcing, documentation, technical programs, and responsible use of AI engineering tools.