Data Analyst

• Collect, abstract, analyze, and accurately code complex clinical data for trauma patients, capturing 88–200 data elements per case from both electronic and paper medical records.
• Apply advanced knowledge of trauma coding standards, including Abbreviated Injury Scale (AIS), ICD-10 coding, trauma scoring methodologies (GCS, ISS, TRISS, POS), and other regulatory requirements.
• Determine case inclusion and ensure compliance with standards established by the American College of Surgeons (ACS), National Trauma Data Bank (NTDB), Trauma Quality Improvement Program (TQIP), and the Massachusetts Department of Public Health (DPH).
• Partner closely with the Trauma Medical Director, Trauma Program Manager, and Performance Improvement team to support trauma quality initiatives, mortality and morbidity reviews, and performance improvement meetings.
• Identify, document, and track clinical complications while ensuring timely performance improvement loop closure.
• Prepare and submit required state and national trauma registry data and maintain ongoing compliance with accreditation and benchmarking requirements.
• Produce routine, ad hoc, and complex reports that support clinical research, operational decision-making, accreditation activities, and quality improvement initiatives.
• Serve as the liaison between the Trauma Program, State Medical Examiner's Office, Health Information Management, Information Technology, and the trauma registry vendor to ensure database integrity and timely issue resolution.
• Participate in trauma rounds, multidisciplinary meetings, educational activities, and ongoing performance improvement initiatives.

Trauma Registrar, Data Analyst

• Own Foley's enterprise data model
• Drive the medallion architecture from a product definition perspective
• Own Silver and Gold layer data definitions
• Prioritize the engineering backlog in partnership with the VP of Engineering
• Be the primary data platform partner for business stakeholders
• Own stakeholder communication
• Maintain a weekly touchpoint with the AI Value Creation Office
• Own delivery against quarterly KRs
• Own the product roadmap for Foley's intelligence self-service platform
• Own the API layer as a product
• Define and maintain the metric layer
• Partner with the data analyst and engineering to enable self-service intelligence
• Drive platform adoption and capability enablement across the organization
• Own the capabilities and paved paths backlog

Staff Product Manager, Data & Analytics

• Works closely with department roles and cross-functional study team members to create data capture solutions that support the quality and timely delivery of data
• Complies with applicable SOPs and work practices
• Learns Pfizer database technologies
• Develops knowledge of data capture tools and methods that support the accuracy and integrity of study data

Database Analyst – Clinical Data Collection Strategies

• Contribute to research projects through idea generation, data preparation, statistical analysis, and development of actionable recommendations
• Evaluate innovative techniques to extract tradable signals from large datasets
• Research and develop advanced model construction methodologies
• Enhance the team’s research infrastructure, production systems, and analytics capabilities
• Present research findings to key stakeholders and develop thought leadership content
• Monitor and analyze factor and model performance, and providing regular insights within the firm
• Perform due diligence on model output, and address inquiries from investment teams

Quantitative Equity Analyst

• Lead the development, governance, and continuous improvement of global supply chain reporting and analytics frameworks
• Translate business and transformation priorities into clear analytics requirements and performance metrics
• Partner with digital and/or technology organization to automate reporting processes
• Ensure data integrity, consistency, and standardization across reporting solutions
• Drive adoption of analytics tools and reporting solutions through stakeholder engagement
• Identify trends, risks, and opportunities across supply chain operations and communicate insights clearly to senior leadership
• Contribute to the roadmap for analytics enablement, including process improvements, automation, and scalability of reporting capabilities

Manager, Reporting – Analytics

• Lead the development, governance, and continuous improvement of global supply chain reporting and analytics frameworks to support strategic and operational decision-making.
• Translate business and transformation priorities into clear analytics requirements and performance metrics aligned to Global Supply Chain objectives.
• Partner with digital and/or technology organization to automate reporting processes and enhance data compilation and visualization capabilities.
• Ensure data integrity, consistency, and standardization across reporting solutions by establishing governance, controls, and best practices.
• Drive adoption of analytics tools and reporting solutions through stakeholder engagement, training, and change management support.
• Identify trends, risks, and opportunities across supply chain operations and communicate insights clearly to senior leadership.
• Contribute to the roadmap for analytics enablement, including process improvements, automation, and scalability of reporting capabilities.

Manager, Reporting & Analytics

• Conduct detailed analyses of business processes and requirements.
• Translate business requirements into actionable specifications for technical teams.
• Develop and implement strategies to achieve business goals.
• Collaborate with stakeholders to understand their needs and gather requirements.
• Evaluate current business processes and systems to propose improvements.
• Perform data analysis to support decision-making processes.
• Create clear and concise documentation including business requirements, functional specifications, and test plans.
• Assist in project management activities such as planning, scheduling, and coordination.
• Conduct user acceptance testing and provide post-implementation support.
• Stay updated with industry trends and best practices in business analysis.

Business Analyst, Speech Analytics

• Conduct and deliver primary research: Ensure that a modern data foundation that includes data quality, governance and context-ready data amplifies development of analytics, data science, ML, and AI internal products.
• Help clients activate, measure, and scale the use of analytics, data science, ML, and AI for business-focused outcomes and use cases.
• Drive alignment among internal stakeholders on data and analytical priorities that support business impact.
• Create approximately eight to 12 high-quality, actionable, analytically deep, and fact-based research projects per year, which include a mixture of written reports, tools, webinars, videos, blogs, podcasts, infographics, and other intellectual property.
• Work alongside sales and marketing teams to promote visibility for this research.
• Drive and lead key Forrester Wave™ and Landscape reports, which are deep, objective evaluations of the most important vendors of data, analytics, and AI technologies.
• Consult clients to apply Forrester’s research in the context of their specific business environment and help solve their problems through short-term and longer-term consultative engagements.
• Present at Forrester-sponsored and industry-related events, as well as deliver client webinars.
• Establish an industry presence as an influential speaker and thinker, build relationships with journalists who cover the sector, and participate in press inquiries as necessary.
• Support business development and prospect conversations as arranged by Forrester’s account leadership teams.
• Foster a style that drives a culture of cross-team collaboration, mentorship, integrity, and relentless and positive pursuits.

Senior Analyst, Data, Analytics and Machine Learning

• Working in a fast-paced, innovative, and change-oriented work environment
• Using programming skills to explore, examine and interpret large-scale data in various forms
• Determine the appropriate techniques to manipulate complex high-volume data, develop insights through analysis and modelling, evaluate business problems, and improve our analytical speed-to-insight
• Perform data mining and analyzing of structured and unstructured data associated with claims, policy, payment activities to solve complex business problems using advanced techniques and leveraging industry cutting-edge technology
• Focus on automation and utilizing technology to provide repeatable reporting solutions to promote self-service culture for business partners
• Building a strong network of peers and mentors
• Attending on-site technical and professional development classes
• Presenting accomplishments to leadership across the organization
• Participating in sponsored community service events

Data Analytics Co-Op

• Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.
• Create scalable, interoperable, and AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence domains.
• Establish the data architecture, integration strategy, metadata framework, and productization approach needed to support semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications.
• Define the future-state scientific data ecosystem and ensure high-quality data products are delivered to support translational science and patient safety initiatives.
• Build AI reasoning models to support data-driven translational safety decision making.
• Define and execute a scientific data product strategy supporting Discovery Research, Translational Science, Preclinical Safety, Clinical Development, Pharmacovigilance, Real-World Evidence.
• Design integration frameworks connecting heterogeneous scientific data sources and define data harmonization strategies spanning SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data.
• Lead design and implementation of curated datasets, semantic-ready data products, feature stores, metadata products, scientific data services, and AI-ready data assets.
• Define metadata standards and data quality frameworks, implement lineage, provenance, traceability, and FAIR data principles.

Principal Scientist, Data Science – Data Products, Integration & Analysis

• Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development
• Create scalable, interoperable, and AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence domains
• Establish data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications
• Define the future-state scientific data ecosystem
• Build AI reasoning models to support data-driven translational safety decision making
• Partner with Amazon engineering and deployed platform resources to deliver scalable data pipelines and data products
• Define implementation strategy for scientific data products deployed on AWS, ensuring alignment with enterprise architecture, security, governance, and AI-readiness requirements

• Drive the next phase of data and analytics for marketing, elevating our site analytics and measurement frameworks and general analysis and insights.
• Drive high-level actionable analysis and insights to inform marketing strategic.
• Lead the next evolution of data and insights for marketing, identifying gaps and ensuring key reports, tools provide the right level of information.
• Deeply integrate with cross-functional data and analytics teams to align on the adoption of advanced analytical techniques by proactively collaborating with Data Science and Data Engineering teams to operationalize complex models and features.
• Operate with high autonomy in a high-pace, agile environment, owning the delivery of high-impact strategic insights.
• Lead and bring to life our unified measurement framework, pulling together MMM, MTA and experiments to support the team in making informed spend decisions.
• Proactively deliver strategic, high-value analysis and recommendations to directly influence marketing channel plans across email, SEO, paid channels and more.
• Drive analysis and insights on site performance, champion the usage of Google Analytics alongside internal site data.
• Conduct deep dives and analyses into performance of marketing campaigns and channels.
• Support forecasting of annual and monthly campaign performance with the finance team.
• Design, execute, and interpret A/B tests and multi-variate experiments to rigorously measure the causal impact of multi-channel strategies.
• Initiate and drive proactive data exploration to uncover opportunities, risks, and performance drivers across the business and marketing.
• Champion data literacy and the output of the analysis team by presenting strategic findings and actionable recommendations to cross-functional teams and executive-level stakeholders.
• Partner with cross-functional teams, agencies and vendors to develop deep understanding of data sources and data collection as well as plans and strategies.
• Prioritize and effectively communicate work plans, ensuring alignment with goals and teams.

Senior Manager, Marketing Analytics

• This position plays a critical role in advancing IH&S’s finance data transformation initiatives by focusing on developing and maintaining Power BI dashboards, enabling standardized financial reporting, and translating complex financial and operational data into clear, decision-ready insights.
• Building data models and creating processes for monthly, quarterly, and annual financial reporting cycles, ensuring accuracy, consistency, and timeliness of data.
• Analyze financial and operational data to identify ways to capture and report on trends, variances, risks, and opportunities, and present findings to finance leadership.
• Partner with Finance, Accounting, Commercial, IT, and Operations teams to ensure data consistency, and alignment between the tools (dashboards/reports) used for financial reporting and to monitor business performance drivers.
• Maintain and prioritize reporting and analytics backlogs leveraging the Agile framework.
• Support executive-level reporting by creating clear, concise, and visually compelling dashboards and summaries.
• Contribute to finance and business transformation initiatives, including automation of reporting processes and improvement of data accessibility and usability.
• Support various workflows by developing financial KPI calculation logic, creating PBI visuals for leadership consumption.
• Support standardized reporting frameworks and ongoing transformation initiatives related to forecasting, reporting standardization, and data governance.

Data Analyst, Finance

• Work with cross-functional project teams in the design and development of high-quality deliverables for clients.
• Collaborate with leadership to define project scope, approach, and development strategies.
• Contribute to Beghou’s internal data warehouse build.
• Demonstrate knowledge of data platform components (warehouse, monitoring, etc.) and data engineering (ETL design, schema design, etc.) and CI/CD best practices.
• Analyze data, synthesize findings, and develop actionable insights, communicating results to both internal and external teams.
• Work on projects, handling client communications, meeting facilitation, and timelines, serving as a primary point of contact with minimal oversight.
• Develop and optimize data processes, utilizing coding where necessary to facilitate efficient data handling and reporting.
• Coordinate with global and diverse teams to ensure seamless project execution.
• Contribute to internal firm initiatives to drive organizational growth.

Data Analytics Consultant

• Collect, organize, and maintain sustainability program data from online initiatives and engagement activities.
• Track participation, engagement, and learning outcomes related to sustainability programs for online students.
• Assist with creating surveys, forms, and assessment tools to gather feedback and measure program effectiveness.
• Analyze data and identify trends, opportunities, and areas for improvement.
• Develop dashboards, reports, infographics, and data visualizations that communicate program impact.
• Support the collection and analysis of data for annual sustainability reports and strategic planning initiatives.
• Research sustainability benchmarks, best practices, and emerging trends relevant to higher education and online engagement.
• Collaborate with other Eco Reps to evaluate the effectiveness of campaigns, events, workshops, and educational programs.
• Present findings and recommendations to the Office of Sustainability staff and student teams.
• Maintain accurate records and documentation of sustainability-related metrics and outcomes.
• Assist with measuring participation in sustainability challenges, online learning opportunities, and virtual engagement initiatives.
• Support data-informed decision-making by providing actionable insights and recommendations.
• Monitor engagement metrics for online sustainability programming, newsletters, social media campaigns, webinars, and virtual events.
• Analyze participation patterns among online students to identify opportunities for increased engagement.
• Evaluate the effectiveness of virtual sustainability education initiatives and recommend improvements.
• Assist in developing metrics that capture the impact of sustainability programs on online learners.
• Support virtual focus groups, surveys, and feedback collection efforts.
• Compile monthly and semester impact reports.
• Track sustainability engagement goals and key performance indicators (KPIs).
• Assist with data collection for STARS reporting and other institutional sustainability assessments.
• Create visual summaries and presentations that communicate results to campus stakeholders.
• Support the development of data-driven recommendations for future sustainability initiatives.

Online Data Analytics Eco Representative

• Define and execute enterprise strategies for Data, Integration, Analytics, and AI capabilities aligned with business objectives and enterprise architecture.
• Develop and maintain multi-year roadmaps that advance data modernization, analytics transformation, AI adoption, and integration capabilities.
• Identify strategic opportunities to improve business outcomes through data-driven decision making and intelligent automation.
• Partner with business and technology leaders to align investments with enterprise priorities and long-term growth objectives.
• Lead a portfolio of enterprise data, integration, analytics, and AI initiatives from concept through value realization.
• Establish prioritization frameworks, governance processes, and delivery models that maximize business value.
• Drive program execution, risk management, resource planning, and executive reporting across strategic initiatives.
• Ensure initiatives are delivered successfully while meeting business objectives, quality standards, and financial targets.
• Serve as a trusted advisor to senior business and technology leaders.
• Translate business priorities into technology and analytics strategies that drive measurable outcomes.
• Build strong partnerships across Commercial, Operations, Supply Chain, Finance, Quality, Manufacturing, and R&D organizations.
• Communicate vision, strategy, progress, and business value to executive stakeholders.
• Establish governance frameworks that ensure scalable, secure, compliant, and reusable enterprise solutions.
• Drive adherence to enterprise architecture principles, data governance standards, privacy requirements, and regulatory expectations.
• Promote consistency, standardization, and reuse across enterprise data and integration ecosystems.
• Define and monitor key performance indicators that measure business value, adoption, solution quality, and delivery effectiveness.
• Drive enterprise adoption of advanced analytics, AI, machine learning, and intelligent decision-support capabilities.
• Identify and prioritize high-value opportunities that leverage analytics and AI to improve business performance.
• Enable development of modern data products, semantic layers, self-service analytics, and conversational intelligence solutions.
• Foster innovation through emerging technologies and industry-leading practices.
• Lead and develop high-performing global teams consisting of employees, contractors, and strategic partners.
• Create a culture of accountability, innovation, collaboration, and continuous improvement.
• Mentor leaders and team members to strengthen technical, business, and leadership capabilities.
• Develop workforce strategies, succession plans, and talent pipelines to support future organizational needs.
• Establish organizational goals and objectives aligned with broader business and technology strategies.
• Champion inclusion, diversity, equity, and employee engagement across the organization.
• Support portfolio planning, budgeting, investment prioritization, and financial management activities.
• Partner with strategic vendors and technology providers to enable successful execution of business objectives.
• Drive cost optimization and value realization across technology investments and initiatives.

Senior IT Manager – Data, Integration & Advanced Analytics

• Oversee a team of analysts responsible for producing accurate, timely, and validated reports from our Complaint Handling and other quality systems.
• Support business decisions, regulatory submissions and audits, and inform strategic decisions within the Quality function.
• Lead the strategy, prioritization, and execution of Quality data initiatives that improve data quality, access, automation, self-service analytics, visualization, and insight generation across the Quality organization.
• Direct and oversee a dynamic team of advanced developers and analysts that plan and execute actions, develop tools and reports, and provide insights on Quality data.
• Establish and maintain effective working relationships with key stakeholders across the Enterprise with a focus on Quality and IT.
• Manage a growing portfolio of data and analytics assets and information technology infrastructure to ensure continuity and continuous improvement.
• Establish and maintain management mechanisms to drive team accountability, execution, effective communication, and cohesion.
• Oversee initiatives that drive continuous improvement with a focus on efficiency and automation.
• Manage vendor relationships and contracts.
• Represent and support the Quality Data Analytics function in audits and regulatory inquiries.

Quality Applications Manager – Quality Data Analytics

• Partner with business units to understand the purpose, usage, storage, access, retention, and sharing patterns of unstructured data across collaboration platforms, file shares, and repositories
• Conduct interviews, workshops, assessments, and discovery sessions with business data owners and subject matter experts to identify current-state practices and gaps
• Elicit, document, and manage business requirements related to records identification, retention, sensitivity, access, sharing controls, business purpose, disposal, and information handling
• Ask for appropriate data taxonomy, labeling, lifecycle, ownership, and control questions to ensure business requirements are complete and actionable
• Translate business needs into user stories, requirement documents, process flows, decision trees, and implementation recommendations for governance and technical teams
• Facilitate conversations around Microsoft Purview-related controls in business-friendly language, including labeling, access constraints, retention approaches, and protection behaviors
• Identify opportunities to improve repository strategy and recommend more effective or modernized solutions where legacy approaches no longer align with current business needs or risk expectations
• Support remediation planning by helping business areas prioritize cleanup, classification, retention alignment, and governance improvements
• Develop process documentation, communications materials, FAQs, stakeholder guides, and business-facing training support
• Assist in preparation for data discovery, audit support, cyber response readiness, tabletop scenarios, and control validation activities
• Monitor progress of business workstreams and support issue identification, dependency tracking, and follow-up actions
• Maintain organized documentation and evidence to support governance, auditability, and repeatable process execution.

IT Data Governance Analyst

• The Manager, Compensation Data and Analytics works in the Corporate Compensation team and assists with reporting and data visualization using a vast array of reporting tools and code base analysis.
• Build robust ETL workflows in Alteryx.
• Automate system administration with PowerShell.
• Develop interactive Tableau dashboards.
• Utilize JavaScript to integrate analytics into broader application ecosystem.
• Bridge the gap between complex data extraction, automation, and visually compelling business intelligence.
• Testing and ensuring the quality of core data, reports and tools.
• Define, interpret and analyze problems in terms of system requirements and suggest modifications to the system design.
• Partner with technology team to set up and improve existing data infrastructure.
• Assist with issue resolution processes, communicate project milestones to all levels of the Compensation organization.
• Create complex data visualizations for executive presentations.
• Work with cross functional groups to support delivery of compensation tools and analytics.

Manager, Compensation Data and Analytics

• Query and analyze large datasets to extract and communicate meaningful insights.
• Build and maintain interactive dashboards and reports using SQL, Python, and BI platforms (e.g., Looker, Omni, Sigma).
• Build and apply machine learning models in Python — from predictive modeling (e.g., cancel/churn prediction, demand forecasting) to applied techniques (e.g., clustering, regression) that generate deeper analytical insight.
• Train and support teams on the data assets you build, so they have what they need to self-serve.
• Own forecasting and experimentation initiatives end-to-end, from framework design through measurement and recommendation.
• Partner with stakeholders across the business to understand what they actually need and provide data-driven solutions.
• Produce clear reports, visualizations, and presentations for leadership, with the ability to influence decisions without formal authority.
• Monitor and report on key performance indicators and emerging trends.
• Assist with ad hoc projects and tasks as necessary.

Data Analyst jobs in Massachusetts

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Trauma Registrar, Data Analyst

Staff Product Manager, Data & Analytics

Database Analyst – Clinical Data Collection Strategies

Quantitative Equity Analyst

Manager, Reporting – Analytics

Manager, Reporting & Analytics

Business Analyst, Speech Analytics

Senior Analyst, Data, Analytics and Machine Learning

Data Analytics Co-Op

Principal Scientist, Data Science – Data Products, Integration & Analysis

Principal Scientist, Data Science – Data Products, Integration & Analysis

Senior Manager, Marketing Analytics

Data Analyst, Finance

Data Analytics Consultant

Online Data Analytics Eco Representative

Senior IT Manager – Data, Integration & Advanced Analytics

Quality Applications Manager – Quality Data Analytics

IT Data Governance Analyst

Manager, Compensation Data and Analytics

Senior Data Analyst