Top Data Analyst Jobs in Boston, MA

The Principal Data Analyst will manage paid media analytics and operations, ensuring data quality, compliance, and actionable insights while collaborating with media buyers to improve performance and ROI.

Partner with Sales, Product, Engineering, and Operations to build the GTM analytics foundation for a new dealer software pillar. Own pipeline, install base, churn, demo-to-close, and launch analytics; identify and fix Salesforce/process gaps; create prospecting and churn-risk signals; write production-grade SQL on Snowflake and productionize assets in dbt; and maintain dashboards in Looker, Omni, and Salesforce CRM Analytics to drive measurable go-to-market execution.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

Manage HMDA and CRA data integrity, perform validation and quality control, coordinate annual LAR and CRA submissions, resolve data discrepancies with cross-functional teams, maintain documentation and controls, support regulatory exams and audits, monitor regulatory changes, and prepare management reporting on data quality and submission readiness.

As a Principal Analyst in Growth Marketing, you will lead analytics for acquisition channels, applying advanced analytical techniques to drive business growth and improve marketing performance while collaborating across teams.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

As a Lead Data Science Analyst, you will develop predictive models, conduct statistical analyses, and create AI-driven solutions to enhance GTM strategy and customer outcomes.

The Principal Data Analyst will manage pricing and profitability strategy for Workhuman's E-commerce store, leveraging data analysis and cross-functional collaboration to drive decision-making and implement improvements in pricing strategies.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

The Lead Investment Data Analyst will design and operate data solutions, manage data quality, and mentor a team while collaborating with various business units.

Serve as the bridge between business and the Product Master Data Management (PMDM) solution: gather and translate requirements, lead UAT and training, prioritize product backlog with Product, monitor tool performance with analytics, support tickets and root-cause analysis, and drive change management to optimize item lifecycle processes.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

Lead end-to-end marketing performance measurement, develop analytics frameworks, deliver insights, and drive business outcomes through advanced analytics and stakeholder collaboration.

This role leads reporting and analytics for business transformation, managing data requirements and collaborating across teams to enhance reporting processes.

Contract Data Analyst to design and maintain Power BI reports and dashboards, build and optimize semantic data models with DAX and Power Query (M), perform ETL using Power Query and Python/PySpark, tune performance, and document data models and processes while collaborating across BI, engineering, and governance teams.

Own and validate quantitative financial datasets used for factor and risk models: onboard and reconcile vendor sources, build automated data validation/monitoring, investigate anomalies, write Python/SQL pipelines, maintain documentation and runbooks, and collaborate with internal teams and vendors to productionize and maintain reliable data workflows.

The Senior Actuarial Data Analyst will support data initiatives, lead projects, analyze data, ensure regulatory compliance, and mentor junior analysts.

The Senior Business Data Analyst handles complex data analyses, collaborates with stakeholders, documents technical specifications, and develops data solutions to meet business objectives, ensuring quality and compliance.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

Lead analytical projects, develop quantitative models, analyze datasets for insights, and translate findings into business recommendations, primarily supporting client decision-making.

Partner with GTM, Clinical Strategy, and Finance to build and maintain dbt models, client-facing reports, and dashboards. Perform SQL-based analyses, ROI and clinical outcomes reporting, and translate insights for non-technical stakeholders. Ensure data reliability through testing, code review, and collaboration with Data Engineering; support ad-hoc requests and automation of reporting.

The Data Analyst will analyze economic data, collaborate with teams, build pipelines, generate insights, and communicate findings through presentations and publications.