Top Data Analyst Jobs in Boston, MA

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.

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.

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.

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

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.

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

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.

Turn complex data into actionable insights for National Accounts by performing statistical analysis, forecasting, modeling, and automated reporting. Build dashboards and executive presentations, diagnose data quality, partner with account teams, data engineers, and finance to influence decisions and track performance metrics.

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

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.

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.

The role involves operating and improving AI-driven data quality pipelines, managing offshore teams, and ensuring data accuracy and reliability. Responsibilities include monitoring pipeline performance, refining rules, and collaborating across teams to enhance data operations.

Perform independent healthcare analytics projects for clients: use statistical tools, predictive modeling, BI/reporting and data visualization. Build reports and insights using R, SAS, SPSS, Cognos, and Business Objects, and collaborate with the Senior Consultant to maintain client relationships.

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.

As a Data Analyst, you will enhance analytical models, analyze model outputs, support data solutions, and communicate findings effectively.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Designs and implements automated ETL pipelines and reproducible workflows. Performs complex statistical analyses and machine learning, cleans and merges observational/medical data, builds dashboards and reports, defines data standards, and collaborates with IT to scale analytics infrastructure and automate analyses for decision-making.

Lead analytics projects by building automated ETL pipelines, performing complex statistical and machine-learning analyses, and producing dashboards and reports. Collaborate with IT/data engineering to scale analytics, enforce data standards, and validate integrated datasets. Work focuses on health-related data and reproducible, performance‑optimized workflows for large datasets.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.