Top Data Analyst Jobs in Boston, MA

Analyzes operational and vehicle inspection data, builds and maintains reports, dashboards, queries, metrics, and data processes, and delivers insights to Operations and leadership. The role cleans and transforms large datasets, validates data quality, supports data science and engineering teams, develops monitoring systems, and presents trends and recommendations for business decisions. It also partners with product, dispatch, quality assurance, and technology teams on operational data and reporting needs.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Analyze data and develop semantic models for certified data products covering rebates, sales-to-GMR, and inventory. Build and rationalize Power BI dashboards, collaborate with Finance and business stakeholders on requirements and user acceptance testing, and consolidate reports into certified data products. The role requires expertise in Power BI semantic modeling, DAX, advanced SQL, Athena, Redshift Spectrum, dimensional modeling, and star schemas.

Designs and maintains SQL/Python data pipelines, warehouse models, and Power BI dashboards supporting finance planning, forecasting, budgeting, and book close. Owns solution architecture from requirements through deployment, validates data and systems, resolves process and reliability gaps, and manages multiple enhancements. Collaborates with business and technical stakeholders, mentors analysts, leads continuous improvement, documents solutions, trains users, and develops automated and AI-enabled efficiencies.

Analyze and visualize large customer datasets, build production-grade data models and scalable data products, automate manual analytical workflows, and create AI-assisted, conversational, and self-service analytics experiences. Translate ambiguous stakeholder needs into actionable solutions while collaborating across teams and experimenting with generative AI and modern data technologies.

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.

Develops and supports business intelligence solutions for a healthcare organization using Epic Cogito, Workday, Symplr, Qlik, and related tools. Creates reports, extracts, visualizations, KPIs, and data models; validates data; resolves anomalies; and advises clinical, administrative, and business users. The role also supports data architecture strategy, analytics tool improvements, data quality, and actionable operational insights while collaborating with organizational leadership and end users.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Leads advanced analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, dashboards, and management reporting. Develops data standards, quality frameworks, automation, and infrastructure strategies while ensuring federal compliance. Coordinates cross-functional analytics projects, supports healthcare quality measures, mentors junior staff, and promotes data-driven decision-making using Python, R, SQL, statistical methods, and machine learning.

Lead complex SQL-based analyses of customer, marketing, ROI, and business data. Translate findings into actionable recommendations, reports, presentations, customer QBRs, and strategic insights. Guide Business Data Analysts, establish analytical best practices, prioritize requests, automate reporting, and collaborate with Customer Success, Marketing, Product, and Operations teams.

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

Deliver recurring and ad hoc commercial analytics, client reporting, performance-guarantee calculations, dashboards, and value measurement. Define and govern metrics, validate data, improve documentation and workflows, and automate repeatable processes. Partner with Client Success, Commercial, Finance, Product, and Analytics teams to translate complex questions into actionable insights, client-ready narratives, and recommendations that strengthen client relationships and inform business strategy.

Analyze automotive marketing and inventory data using complex SQL queries, investigate CRM and data discrepancies, standardize external data sets, maintain client-facing BI dashboards, and perform rigorous data quality assurance. The role also involves resolving Jira and HubSpot tickets, fulfilling ad hoc analytical requests, and collaborating with a US-based reporting team in English.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Supports risk portfolio programs through strategic project planning, data analysis, dashboard development, process automation, vendor and ROI management, governance, and audit documentation. The role partners with risk analysts, data scientists, Product Management, Engineering, and other stakeholders to identify risk indicators, design controls, improve workflows with AI tools, and communicate actionable insights across credit, fraud, and reputational risk initiatives.

Analyze complex data to support company-wide decisions, building metrics, scalable data pipelines, dashboards, and reports. Partner with cross-functional teams and leaders to translate business needs into data problems, deliver actionable recommendations, and improve self-service reporting. The role also involves data storytelling, stakeholder training, and enabling data literacy. Preferred experience includes Spark, Python, statistical analysis, leadership reporting, software development practices, and AI tools.

Develops Power BI dashboards, reports, queries, and ad-hoc analyses for supply chain operations and strategic decisions. Translates business needs and integrated data into actionable visualizations, enhances data integration and maturity, and identifies root causes through descriptive and prescriptive analytics. Collaborates with business, technology, analysts, and data scientists on agile product development, supports innovation, and helps junior team members succeed.

Develop Power BI dashboards, reports, and queries that translate complex supply chain data into business solutions. Partner with operations and technology teams to prioritize analytics requests, perform ad hoc analysis, identify root causes, and support strategic decisions. Use Azure Data Lake, SQL, ETL tools, and agile methodologies to improve data integration and maturity while collaborating with analysts, data scientists, and business stakeholders.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Analyzes operational data, builds and maintains reports and Power BI dashboards, develops data processes and pipelines, validates data quality, monitors KPIs, and presents insights to leadership. Partners with Operations, Quality Assurance, Dispatch, engineering, data science, and product teams to answer business questions, improve reporting, support analytical projects, and inform operational decision-making.

Analyze healthcare and clinical operations data to deliver actionable customer insights, physician performance reporting, care-quality dashboards, and scalable BI solutions. The role requires SQL-based data transformation, dashboard development, collaboration with clinical, product, engineering, and client-facing teams, and clear communication of findings. The analyst will also use AI tools for query generation, data cleaning, pattern recognition, and analytical summaries.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Analyzes marketing and CRM data, builds KPI dashboards, provides campaign and business development recommendations, and manages Salesforce administration, automation, audits, permissions, and data quality. The role validates integrations, supports migrations, troubleshoots system discrepancies, identifies enrichment opportunities, and provides user onboarding, training, and documentation. It collaborates across marketing and business development teams to improve prospecting, relationship management, cross-selling, client acquisition, and retention.