Top Data Analyst Jobs in Boston, MA

Leads healthcare quality analytics using hospital performance, national rankings, Medicare claims, and CMS data. Replicates quality methodologies, identifies improvement opportunities, builds dashboards and benchmarking tools, and establishes analytic validation standards. Presents insights to executives and customers, supports pre-sales and engagements, partners with data scientists and consultants, and mentors analysts.

Own analytics as an internal data product across GTM, People, Finance, and related functions. Translate ambiguous business questions into self-service data solutions, deliver executive-ready narratives, manage stakeholder priorities, and guide data-driven decisions. Serve as a marketing analytics subject matter expert across attribution, campaign measurement, lead tracking, funnel analysis, predictive modeling, and experimentation. Use SQL, modern data-stack tools, BI platforms, and AI-assisted modeling to deliver actionable insights.

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.

The Senior Data Analyst will lead metrics definition, reporting, statistical analysis, experimentation, dashboard management, and pricing analytics. The role involves building data pipelines, collaborating with data engineers on data assets and feature stores, investigating complex business questions, and translating analytical findings into strategic recommendations for product, pricing, and senior leadership. Strong SQL, statistics, econometrics, communication, and cross-functional collaboration skills are essential.

Leads development and delivery of complex healthcare, clinical, provider, and financial datasets. Provides enterprise reporting, dashboards, data visualization, business intelligence, and decision support. Analyzes cost, utilization, provider, member, and clinical data to identify inefficiencies and savings opportunities. Serves as an internal analytics consultant, improves data procedures, automates reporting processes, trains team members, and ensures validation and documentation standards.

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

Supports public health data extraction, management, cleaning, validation, harmonization, statistical and qualitative analysis, and evaluation. Develops analytic datasets and documentation, analyzes implementation and outcome measures, integrates mixed-methods data, and prepares technical memoranda, reports, tables, figures, and presentations. The role also uses Microsoft Office and CDC administrative systems while supporting government program monitoring and evaluation activities.

Supports a global Microsoft Dynamics 365 ERP integration strategy by configuring Finance & Operations and Customer Engagement modules, establishing legal entities, defining business requirements, and resolving system and data issues. Leads functional testing, UAT, deployment, test automation, quality assurance, and data migration validation. Collaborates with legal, finance, operations, and technical teams to improve business processes, automate workflows, close process gaps, and ensure accurate, effective ERP implementations.

Analyzes servicing, collections, application funnel, and contact-center data to identify performance gaps and inform business decisions. Builds automated reports, partner data files, Snowflake and dbt models, and operations dashboards. Maintains metric definitions, audits models, reconciles partner data, and develops business-case analyses. Uses AI tools to improve analytics workflows and collaborates with data engineering, product, and business teams.

Analyzes data and builds analytical datasets, data models, SQL queries, Python notebooks, dashboards, and reports using Databricks and BI tools. Identifies trends, validates data quality, translates business requirements into reporting solutions, documents data logic, and communicates insights to technical and non-technical stakeholders. The role also supports governance, security, lineage, and compliance across collaborative client delivery projects.

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.

Develop resource allocation, demand forecasting, and capacity models for Customer Success. Analyze quantitative and qualitative data, identify trends and risks, and translate findings into actionable recommendations. Partner with finance, planning, delivery, and leadership stakeholders to refine assumptions, resolve complex business issues, and support regional implementation. Present insights to senior leaders and manage cross-functional priorities in an ambiguous, fast-paced environment.

Supports information collection and organization for manuals, training materials, installation guides, proposals, and reports. Edits technical and customer-facing documentation, assists with financial and administrative tasks, and maintains systems, operations, and procedural documentation libraries. Collaborates remotely with project managers, requirements analysts, Scrum Masters, developers, testers, and government stakeholders in Agile ceremonies while complying with CUI and cybersecurity requirements.

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.

Design and maintain scalable AWS-based data pipelines, architectures, ETL/ELT workflows, databases, and big data solutions. Integrate and transform complex datasets using Python, SQL, Spark, Hadoop, and Kafka. Build data models, dashboards, reports, and analytics solutions while implementing data quality, governance, security, monitoring, and compliance processes. Support migrations and modernization projects, collaborating with data scientists, analysts, and business stakeholders to deliver reliable, decision-ready data.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Analyze clinical outcomes, engagement, feature usage, ROI, and business trends for client reporting. Build and maintain complex SQL queries, reporting workflows, interactive dashboards, and self-service analytics. Partner with Customer Success, Sales, Marketing, Finance, Product, and Medical Affairs to deliver actionable insights, executive presentations, and client-facing materials. Improve data quality, automate recurring reporting, and identify opportunities that support client outcomes and business growth.

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Leads business, systems, data, and API requirements analysis for digital capabilities aggregating third-party financial data. Translates customer and business needs into requirements, user stories, acceptance criteria, and test scenarios; analyzes integrations, API contracts, data flows, mapping, and normalization. Partners with product, architecture, engineering, and business teams on solution design, ambiguity resolution, risk identification, and business validation.

Translates customer and business needs into requirements for APIs, data platforms, and financial-data sharing solutions. Analyzes API contracts, data models, payloads, integrations, dependencies, and system impacts. Creates user stories, acceptance criteria, process flows, and diagrams; collaborates with product, architecture, engineering, and business teams through solution delivery. Supports testing, validation, release readiness, and product decisions using customer and business insights.

Supports federal data integration for NOAA Fisheries by documenting requirements, analyzing source data structures, performing data mapping, writing user stories and acceptance criteria, facilitating stakeholder workshops, tracking approvals, developing training materials, maintaining traceability matrices, and contributing to progress reports. The role focuses on integrating marine and anadromous species data into a unified Endangered Species Act platform.

The Senior Data Analyst will support Growth and Product teams through paid-channel analysis, user journey optimization, activation and retention insights, and churn reduction. Responsibilities include developing experiments, analyzing ad network performance, improving tracking and instrumentation, ensuring data quality, and enabling self-service analytics. The role requires translating complex data into actionable recommendations and communicating effectively across technical and non-technical teams in a fast-paced SaaS environment.

Lead full-cycle customer data migrations from legacy DME/HME systems into a SaaS platform. Responsibilities include mapping, extracting, cleansing, transforming, and validating patient, inventory, claims, order, and payer data; resolving discrepancies; collaborating with implementation and product teams; supporting customers; and documenting migration processes.

Owns lead and hotel account data quality for a sales organization. Responsibilities include CRM audits, deduplication, enrichment, lead qualification, routing, SLA development, escalation resolution, data workflow documentation, vendor evaluation, SQL-based validation, and responsible use of AI for quality assurance and anomaly detection.

Leads SAP MDG functional design and delivery across master data domains, including requirements, governance, workflows, testing, data migration readiness, stakeholder decisions, and continuous improvement. Guides technical teams on configuration, integrations, and development while owning functional specifications, acceptance criteria, solution decisions, and business sign-off. Requires strong SAP MDG experience, cross-functional leadership, and expertise in Material, Business Partner, and/or Finance master data.