Top Data Analyst Jobs in Boston, MA

Develops and maintains KPIs, dashboards, datasets, and analytical models to measure Medical Affairs impact, resource allocation, performance, and business outcomes. Sources and manages data across systems, identifies trends, supports strategic planning, partners with UI and Medical Affairs stakeholders, resolves data issues, and communicates insights. The role also provides leadership, talent development, and cross-functional collaboration within a pharmaceutical environment.

Leads advanced analytics, reporting, scalable data models, dashboards, and data pipelines supporting Business and Marketing teams. Partners with senior stakeholders and AI Engineering to implement AI and machine learning workflows, predictive insights, and automation. Develops documentation, drives analytics engineering best practices, and mentors team members. Requires strong SQL, Python, APIs, data modeling, stakeholder communication, project leadership, and blockchain expertise.

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.

Lead complex data analysis across Liftoff’s supply-side business, using optimized SQL on large-scale datasets and BI tools to build dashboards, reporting pipelines, and actionable insights. The role conducts root-cause analysis, evaluates experiments, translates technical developments into business impact, leads cross-functional initiatives, and mentors analysts. It partners with Engineering, Product, Data Science, Finance, Commercial teams, and executive leadership to influence roadmap and operational decisions.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Analyze how customers use Hi Marley to guide product, customer success, and company decisions. Define feature success metrics, evaluate adoption funnels, measure pilots and utilization, present customer-facing insights, and establish trusted self-service reporting. Partner with Data Engineering to translate analyses into governed data models and communicate findings clearly to executives and customers.

Maintains client and payment data for leased housing programs, processes monthly checks, reconciles reports, administers invoices and petty cash, applies payment adjustments, troubleshoots software issues, and supports quality control, regulatory compliance, audits, and accurate reporting.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

Leads fraud analytics strategy for digital payments, defining risk frameworks, fraud metrics, and analytical models. Partners with Product, Engineering, and Risk Operations to turn insights into scalable fraud mitigation solutions. Manages external data sources, defines requirements for production data pipelines, and establishes best practices for risk measurement and modeling. Serves as a senior thought leader influencing cross-functional stakeholders and executive decision-makers.

The HR Data Analyst develops and maintains workforce dashboards, KPIs, reports, and automated analytics solutions. They analyze employee lifecycle, engagement, retention, talent, learning, rewards, and HR operations data to identify trends and provide recommendations. The role partners with HR and business leaders, presents insights, ensures data quality and compliance, and improves reporting processes through governance, validation, automation, and data modeling.

Analyzes claims data to identify trends, patterns, risks, and business opportunities. Retrieves, validates, and prepares data from multiple databases; creates reports, dashboards, visualizations, spreadsheets, and presentations; supports forecasting and reporting needs; collaborates with claims, underwriting, product, IT, and leadership teams; and communicates recommendations for business decisions and process improvements.

Build Python and SQL data pipelines, maintain data integrity, automate dashboards and reporting, and deliver actionable analytics. Develop AI- and LLM-assisted workflows for data enrichment, classification, summarization, and process automation. Support leadership decision-making, sales, customer success, and internal efficiency while communicating insights to nontechnical stakeholders. Evaluate, document, and monitor AI solutions for accuracy, cost, risk, and auditability.

Analyze operational data, build and maintain Power BI dashboards, validate data quality, investigate trends and discrepancies, document reporting definitions, and communicate findings to business stakeholders. Partner with IT, data engineering, and analytics teams to resolve data issues and support reliable reporting. Use SQL, Power Query, DAX, Excel, and AI-enabled analytics tools to transform data and inform process improvements.

Supports energy and sustainability analytics for data center clients by cleaning, validating, and analyzing datasets; developing Power BI or Tableau dashboards, dataflows, and reports; documenting methodologies; performing quality checks; and delivering accurate outputs across concurrent projects. Collaborates with energy and sustainability teams, learns internal analytics platforms, and identifies opportunities to improve reporting, automation, and workflows.

Analyzes operational and financial data to identify trends, risks, and opportunities; develops forecasts, regression models, scenarios, dashboards, visualizations, and recommendations for business decision-making. Partners with business leaders to define requirements, communicates insights, and supports data governance, quality, stewardship, modeling, and privacy initiatives.

Analyzes marketing data to guide investment decisions, improve campaign performance, segment customers, support A/B testing, and identify conversion opportunities. Builds dashboards and reports, maintains metric definitions and data quality standards, investigates anomalies, and communicates actionable insights to sales, marketing, and global operations partners.

Analyze case, client, and financial data to build Power BI dashboards, executive and client reporting, recurring Excel deliverables, SQL analyses, and lightweight automations. The role investigates discrepancies, supports ad hoc business questions, documents metric definitions, and partners with operations, sales, finance, and leadership to improve reporting and reduce manual work.

Owns the CX Operations data foundation in Snowflake by designing architecture, governance, data quality standards, and reusable dbt models. Leads complex analyses, dashboards, scenario planning, and executive communication while mentoring analysts and partnering with engineering and strategy teams. Supports AI enablement by creating trusted data models, evaluation standards, and agent performance tracking.

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.

Supports a defense aviation modernization program by integrating and analyzing complex program data across cost, schedule, risk, logistics, testing, configuration management, and cybersecurity. Develops dashboards and executive reports, performs KPI and performance analysis, supports program reviews and aircraft integration efforts, tracks test results and corrective actions, and automates reporting processes. Requires extensive DoD or aerospace experience, aircraft modernization expertise, and an active Secret clearance.

Analyzes operational, engineering, logistics, reliability, maintenance, training, supply chain, and program data for a NATO SATCOM support program. Develops executive dashboards, KPIs, scorecards, predictive reports, trend analyses, and risk assessments. Maintains product support databases, validates data integrity, supports reliability and sustainment analyses, and reports on readiness, quality, cost, schedule, and lifecycle performance. Presents actionable recommendations to technical and executive stakeholders.

Loads, queries, validates, and analyzes data; refreshes databases; prepares client reports; identifies automation opportunities; supports UAT, system implementations, and quality assurance; and collaborates with cross-functional teams. The role requires database management, SQL, Oracle, Unix, Python, Power BI, data modeling, and relational database expertise, with opportunities to use scheduling and master data management tools.

Owns 837 encounter-data file transmissions to state agencies, manages state response files, verifies transaction completeness and accuracy, and resolves errors to meet state requirements. The role requires experience with medical claims, Medicare or Medicaid, FTP and data-transfer software, and data management. Preferred qualifications include Microsoft Access, analytical discrepancy resolution, and working knowledge of 837 claims files.

Leads business analysis for regulatory data and system capabilities across the GRIDS portfolio. Partners with regulatory stakeholders and Digital & Technology teams to elicit requirements, facilitate workshops, assess process and data impacts, create functional specifications and user stories, support Agile delivery, and improve regulatory processes, data quality, and system adoption. Requires substantial life sciences or regulatory business analysis experience and knowledge of Veeva RIM and GxP environments.

Serves as a strategic liaison between regulatory stakeholders and Digital & Technology teams. Elicits and documents requirements, facilitates workshops, translates business needs into specifications and user stories, assesses process and data impacts, supports Agile delivery, and identifies opportunities for regulatory process optimization, data quality improvement, and system capability advancement.