Top Data & Analytics Jobs in Boston, MA

Own wholesale performance reporting and analysis across retail partners, products, and regions. Build datasets, data models, dashboards, and automated reporting while validating data quality. Analyze sell-through, inventory, pricing, promotions, and commercial trends to identify growth opportunities. Partner with stakeholders across Wholesale, Digital Commerce, and Marketing to frame analytical questions, communicate findings, and provide actionable recommendations.

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.

The AI Analyst Co-op will use Python, HTML, SQL, APIs, and AI tools to generate scalable insights for go-to-market teams. Responsibilities include personalizing BDR outreach by buyer persona, distributing market insights across sales, marketing, and partner resources, and collaborating with Platform Advisory. The role requires strong analytical skills, attention to detail, problem-solving persistence, and an understanding of technology’s role in improving operational efficiency.

Leads the Federal Reserve Bank of Boston’s Data & Analytics department, setting strategy, architecture, governance, and multi-year technical roadmaps. Oversees self-service analytics, data infrastructure, pipelines, curated datasets, visualizations, and decision-support tools. Builds stakeholder partnerships, ensures responsible AI use, manages operational risks and controls, and develops a high-performing multidisciplinary team. Represents the function to executive leadership and collaborates across the Federal Reserve System.

Design, build, test, and support scalable cloud data solutions and pipelines. Develop data platforms using Python, Spark, SQL, Databricks, Snowflake, relational and NoSQL databases, and cloud technologies. Establish reusable data engineering patterns, security controls, and operational standards. Collaborate with product managers, engineers, analysts, and data scientists; communicate technical outcomes; mentor data professionals; and deliver resilient, high-performance financial data products.

Supports client data and analytics engagements by designing validation approaches, building data integration and transformation solutions, analyzing data quality issues, testing pipelines with SQL, documenting findings, and recommending corrective actions. The role collaborates with clients, manages workstreams, mentors junior team members, and applies Agile methods while delivering risk and regulatory data solutions.

Manages vendor master data compliance, including reviewing and approving vendor records, validating banking and tax information, maintaining documentation, conducting third-party checks, auditing ERP enrichment, and supporting audit readiness. Partners with vendors, financial institutions, internal teams, and data management support to resolve discrepancies and ensure accurate, compliant vendor data. Provides training and subject-matter expertise while meeting processing timelines, segregation-of-duties requirements, and service-level agreements.

Build AI agents and data acquisition systems, evaluate dataset quality, define quality KPIs, and improve data processes. Partner with product teams to deploy data into customer-facing products and acquire datasets from third parties, including coordinating vendors and contracts. The role requires organizing multiple projects, structuring analyses, communicating tradeoffs, and using data to support investment decisions and customer outcomes.

Lead analytical investigations and build measurement frameworks, dashboards, reporting systems, and reusable Snowflake-backed data products for Customer Experience teams. Partner with data scientists on health scoring, forecasting, segmentation, and validation. Translate ambiguous business questions into decision-ready insights, communicate findings to senior stakeholders, and document solutions for operational handoff.

Supports the development and maintenance of SQL and Python data pipelines, data models, semantic layers, dashboards, and reports. Performs data wrangling and preprocessing, translates business requirements into data solutions, and contributes to data governance, security, and quality assurance. Collaborates with cross-functional teams supporting marketing, engineering, product development, supply chain, finance, business analytics, and AI initiatives.

Build predictive models forecasting customer behavior, analyze retention and gameplay trends, and create automated tools, analyses, and dashboards. Translate model outputs into actionable recommendations that guide marketing investments, promotional strategies, customer valuation, and retention. Partner with Marketing, Finance, Data Science, and Data Engineering teams while using Databricks, Airflow, Bitbucket, SQL, Snowflake, and dashboarding tools to support revenue growth and customer insights.