Top Data & Analytics Jobs in Boston, MA

Leads the Journey Intelligence Team’s analytics strategy, develops analysts, and builds measurement frameworks, segmentation strategies, and scalable data assets. Conducts exploratory analysis, experimentation, and customer lifecycle research to identify engagement opportunities. Partners with Product, Operations, and senior leadership to translate customer behavior insights into strategic initiatives and measurable improvements across the customer journey.

Performs data analysis, cleans and validates data, identifies trends and anomalies, builds dashboards and reports, and supports KPI development. Collaborates with engineers and business stakeholders to improve data quality, pipelines, reporting requirements, and analytical processes. Leads data-driven change management, communicates insights, shares best practices, and may support urgent IT incidents.

This co-op develops analytical solutions for fulfillment performance reporting. Responsibilities include understanding fulfillment processes, consulting on data pipelines, developing data models and dashboards, analyzing trends, and providing insights and recommendations. The role collaborates with product managers, visualization analysts, data scientists, IT, technical teams, and fulfillment operations.

An 11-week analyst internship involving qualitative and quantitative data analysis, performance trend research, opportunity identification, and recommendations supporting business decisions in the insurance industry. Interns collaborate individually and in teams, use analytical and technical tools, participate in training, and develop business acumen while exploring potential full-time opportunities.

Develop market intelligence, forecasting, statistical models, scenario analyses, and automated reporting for supply chain decisions. Integrate internal and external datasets using Python, R, SQL, and other tools; build dashboards; support data governance; and translate analytical findings into recommendations for procurement, planning, and executive stakeholders.

Design, code, test, and deploy software solutions for Tax clients. Collaborate with teams to gather requirements, implement APIs and integrations, apply CI/CD and OOD principles, perform code reviews, debug and QA, and support project delivery while building client relationships and technical skills.

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.

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.

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.