Top Data Analyst Jobs in Boston, MA

The Supply Chain Data Analyst will enhance operational efficiency by managing procurement, auditing supply chain workflows, and exploring automation and AI opportunities.

Build and productize externally consumable data assets from concept to delivery. Define schema, governance, SLAs, documentation, and delivery (Snowflake share, SFTP, API). Partner cross-functionally to productionalize datasets, monitor quality, iterate on customer feedback, and create repeatable productization frameworks.

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.

Analyze customer data and build production-grade data models, dashboards, data products, and self-service analytics capabilities. Automate manual workflows, translate stakeholder needs into scalable solutions, and experiment with generative AI, conversational analytics, and AI-assisted coding tools. The role requires strong SQL, data visualization, analytical problem-solving, business judgment, communication, and collaboration skills. This is a hybrid position requiring three days onsite weekly in Framingham.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Lead product analytics for the Dealer team: run exploratory analyses, build and audit metrics, create dashboards, automate data transformations (dbt/LookML), partner with Data Engineering, and present insights to influence product strategy. Use SQL, Python/R, and GenAI tools to solve complex data problems and improve product performance.

Account Executives at LinkSquares manage the entire sales process, focusing on new customer acquisition through research, outreach, and closing. They prioritize teamwork, quotas, and deadlines while driving business opportunities in a collaborative culture.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

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

Develop scalable, reusable data and reporting solutions, production pipelines, dashboards, and proof-of-concepts. Apply data engineering, quality testing, metadata, lineage, compliance, and security practices while optimizing infrastructure performance, reliability, and cost. Evaluate emerging tools and GenAI applications, collaborate with technical and business stakeholders, prioritize customer value, and mentor junior team members.

Designs and develops scalable, reusable data solutions, production pipelines, reporting dashboards, and proof-of-concepts for business stakeholders. The role includes data engineering, infrastructure optimization, data quality testing, metadata and lineage management, compliance, security, and Gen AI applications. Responsibilities also include evaluating tools, mentoring junior team members, prioritizing customer-focused solutions, and collaborating with technical and non-technical stakeholders.

Develops and manages KPIs, dashboards, datasets, and analytics to measure Medical Affairs impact, resource allocation, and performance. Leads cross-functional analytics projects, mentors data analysts, manages vendors, improves reporting processes, and translates stakeholder feedback into strategic insights. Requires strong pharmaceutical medicine knowledge, including clinical trials, GCP, drug development, regulatory guidance, compliance, and promotional rules.

Designs and develops scalable, reusable data solutions, production pipelines, dashboards, and reporting tools. Builds proof-of-concepts, optimizes data infrastructure, implements data quality testing, and applies metadata, lineage, compliance, and security principles. The role also evaluates data engineering technologies, explores generative AI applications, supports stakeholder needs, prioritizes customer value, and mentors junior team members.

Designs and develops scalable, reusable data solutions, production pipelines, reporting dashboards, and proof-of-concept systems. Responsibilities include data engineering, infrastructure optimization, data quality testing, metadata and lineage management, compliance, security, GenAI applications, and iterative solution testing. The role collaborates with technical and non-technical stakeholders, prioritizes customer value, mentors junior team members, and evaluates emerging data engineering tools and technologies.

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

Clean, structure, and analyze primary market research data using statistical tools; produce client-facing cross-tabulations; perform survey and data quality assurance; maintain databases and data systems; and improve processes while collaborating with research, marketing sciences, and publishing teams.

Own customer experience and delivery metrics, dashboards, and reporting across Support, Professional Services, Customer Success, and Renewals. Analyze customer, operational, usage, and financial data to identify risks, trends, bottlenecks, and renewal threats. Partner with leaders to define KPIs, translate business questions into recommendations, validate data quality, automate reporting, and build self-service analytics. Collaborate with AI teams to measure the impact of AI-driven tools.

Supports vendor and item master data setup, maintenance, and controls across the organization. Serves as a contact for vendors and internal teams, provides guidance and training, monitors compliance, supports audits and risk assessments, analyzes master data, prepares reports, tracks KPIs, resolves issues, and recommends process improvements.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

Maintains Workday human capital data, processes employee transactions, audits records, supports I-9, E-Verify, visa, payroll, and HC inbox operations. Produces workforce reports and analyses, prepares leadership presentations using AI, documents procedures, supports compliance and special projects, and identifies process improvements. Requires strong attention to detail, confidentiality, communication, organization, and advanced Excel and PowerPoint skills.

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.

Analyze and transform data to support project execution, supplier performance, process automation, and financial transparency. Build Power BI dashboards and executive scorecards, automate reporting with Power Automate, extract data from enterprise systems, and maintain KPI reports. Document data models, transformation logic, and workflows while collaborating with engineering, project controls, procurement, IT, finance, and other stakeholders.

Analyzes digital customer and product data to deliver dashboards, reporting solutions, experimentation measurement, journey analytics, attribution insights, and ad-hoc analysis. Partners with Digital Product and Technology teams throughout the product lifecycle, validates data and tracking solutions, supports platform modernization, performs data quality checks, and translates business questions into scalable business intelligence products while maintaining risk and regulatory controls.

Leads advanced people analytics using Workday as the foundation for workforce insights, planning, retention, compensation, and talent decisions. Develops analytical datasets, metrics, dashboards, predictive models, and executive reporting; establishes data definitions, governance, quality controls, and architecture standards. Partners with HR Technology, Finance, HR leaders, and business executives to translate complex workforce data into strategic recommendations. Serves as a Workday and people-data subject-matter expert, mentors analysts, and influences enterprise decisions through clear storytelling.

Own and improve federal data quality, fulfill customer data requests, build tailored data feeds and trackers, and identify patterns for customer insights and marketing thought leadership. The analyst will conduct QA across personnel, organizational, and program data, collaborate with data, product, and engineering teams, and translate data gaps into platform improvements. The role requires basic SQL, analytical writing, attention to detail, and comfort working across competing priorities.