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

• Partner with business stakeholders to understand business objectives, define data requirements, and translate business questions into scalable analytical solutions
• Extract, integrate, validate, and analyze data from multiple internal and external sources to create trusted datasets for reporting and decision-making
• Develop, maintain, and optimize SQL queries, data pipelines, and analytical models using BigQuery, Python, and other data technologies
• Design, build, and maintain recurring and ad hoc reports, dashboards, and analytical outputs that provide meaningful business insights
• Validate data accuracy and integrity by reconciling results across systems, identifying discrepancies, and partnering with stakeholders to resolve data quality issues
• Analyze trends, patterns, and anomalies, presenting findings through clear visualizations and executive-ready insights that support informed decision-making

• Collaborate with colleagues and clients at all levels from your very first day
• Develop tailored solutions for clients around the globe
• Engage in discussions with clients and colleagues to share ideas
• Implement various prototypes while assessing their effectiveness

Analyst – Data & Analytics Team

• Analyze integrated and extensive datasets to extract value, which directly impacts and influences business decisions
• Work collaboratively with key business stakeholders to identify areas of value, develop solutions, and deliver insights to reduce overall cost of care for members and improve their clinical outcomes
• Interpret and analyze data from multiple sources including healthcare provider, member/patient, and third-party data
• Support execution of large-scale projects with limited direction from leadership
• Identify and perform root-cause analysis of data irregularities and present findings and proposed solutions to leadership and/or customers
• Manage multiple, variable tasks and data review processes with limited supervision within targeted timelines
• Support the design, testing, and implementation of process enhancements and identify opportunities for automation
• Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how customers interact with analytic products
• Support multiple functions and levels of the organization and effectively, both verbally and visually, communicate findings and insights to non-technical business partners
• Independently engage with customers and business partners to gather requirements and validate results
• Communicate and present data-driven insights and recommendations to both internal and external stakeholders, soliciting and incorporating feedback when required

Data Analyst II – Healthcare Analytics

• AI & GPU Infrastructure Modeling: Track, evaluate, and forecast cross-environment financial trends driven specifically by AI platform adoptions, machine learning workloads, and enterprise GPU utilization.
• Dataverse Pipeline Integration: Act as the core architect for cloud and data center data collection, building reliable ingestion loops that funnel technical usage data directly into Dataverse.
• Dynamic PO Lifecycle Management: Reform the purchase order framework from an annual forecast model to an active, twice-a-year allocation refresh cycle that keeps pace with AI investment spikes.
• Cross-Functional Bridge Building: Partner directly with workstream service owners and IT engineering teams to translate raw system metrics into shared financial strategies, preventing data misinterpretation.

Senior AI FinOps Data Analyst

• Conduct collision scene investigations
• Conduct vehicle examinations
• Analyze physical evidence, vehicle damage, roadway conditions, photographs, and electronic data
• Download, collect, and interpret Event Data Recorder (EDR) data
• Obtain and analyze Vehicle Sampling Evidence
• Analyze and interpret evidence and data to render an expert opinion pertaining to damage and to confirm or dispute a claim.
• Work independently and manage assignments from intake through final reporting
• Maintain professional documentation and chain of custody standards
• Present findings in the courtroom as an expert.

Collision Data Analyst

• May manage or supervise a small group.
• Proactively monitor and remediate incoming data used in risk measurement and reporting.
• Ensure the completeness, validity, and accuracy of data on a daily basis.
• Work with business data users to define the use of data within risk systems.
• Work closely with technology to ensure the timely and accurate operation of risk models and reporting systems.
• Implement effective risk controls of our data processes and systems.
• Participate in user acceptance testing of data control processes.
• Work with other groups as needed, including Middle Office, Sales and Trading, Technology, Compliance, Operational Risk, and Enterprise Capital Management to ensure effective controls over data for GMRM.
• Establish and maintain compliance with the Enterprise Data Management Standards related to:
• Work with report preparers to document, update and maintain end user (EUC) computing lineage for existing and new Risk Data Aggregation (RDA) reports
• Integration (stitching) and sustainment of EUC and technical PDE data lineage from the report back to one hop outside of Credit Risk
• Maintaining EUC lineage in Enterprise tools (DQC Toolkit)
• Performing quality assurance analysis on data lineage
• Updating asset flow diagrams
• Facilitate validation that the inputs into the Critical Risk Figures (CRFs) are fit-for-purpose including analysis of discrepancies, tracking and coordinating remediation efforts
• Track and report on status of project deliverables

Senior Data Support Analyst

• Identify business intelligence and data analysis needs
• Work closely with Business and Technical teams
• Turn data into critical information for business decisions
• Engage business and development teams to design dashboards, alerts, and reports
• Provide project leadership including facilitating requirements gathering
• Conduct analysis of functional business processes
• Educate clients to use data as an analytical tool

Business Data Analyst

• 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

• Perform hands-on analysis of sales performance across the organization — pipeline, bookings, conversion, and productivity — to answer recurring and ad hoc questions from sales leadership.
• Turn analysis into clear, decision-ready insights and recommendations for a non-technical audience, not just raw reports.
• Build and maintain reporting artifacts, including tear sheets, executive summaries, and dashboards, that give stakeholders a clear, current view of the business.
• Source, validate, and reconcile data across CRM (HubSpot, NetSuite) and ERP (NetSuite, Ormandy) systems to ensure analysis rests on accurate, trusted data.
• Investigate data quality issues and anomalies and recommend improvements to data capture and reporting.
• Structure and maintain the templates and sheets that support the sales forecasting process.
• Support sales territory planning through data preparation, mapping, and scenario setup.
• Partner with Division Leads and leadership to ensure planning and forecasting tools are accurate, usable, and up to date.
• Apply low-code automation (Microsoft Power Automate) to streamline recurring reporting and data preparation, reducing manual effort.
• Build and support basic AI agents or assistants using low-code tools such as Microsoft Copilot Studio where they improve efficiency.
• Identify manual, repetitive analytical tasks and convert them into reliable, repeatable processes.
• Work across the Sales Strategy & Operations organization to understand data and tooling needs and deliver practical solutions.
• Partner with Sales Operations, Finance, and divisional stakeholders to align definitions, data sources, and reporting standards.
• Document tools, workflows, and processes so solutions are maintainable and transferable across the team.

Sales Analytics Specialist

• Conducting quantitative analytics and complex modeling projects
• Leading the development of new models and analytic processes
• Performing end-to-end market risk stress testing
• Identifying continuous improvements through reviews of approval decisions
• Performing statistical analysis on large datasets
• Creating commentary to effectively explain trends and loss projections
• Collaborating across teams to ensure portfolio and business decision impacts are accounted for.

Senior Quantitative Finance Analyst

• Apply quantitative methods and techniques to manage, analyze, and interpret research data.
• Construct, clean, and document large datasets for both internal use and project-specific needs.
• Create customized, presentation-quality reports based on data analysis results.
• Contribute to the design and methodology of research studies.
• Manage administrative components of projects to ensure smooth execution.
• Assist in the preparation of technical procedures, documentation, and reports.
• Write, compile, and edit assigned sections of proposals and project deliverables.
• Review work products to ensure accuracy, clarity, and consistency of content.

Medicaid and Prescription Drug Data Analyst

• Build business case analyses, financial models, and analytical frameworks that support decisions across pricing, retention, expansion, margin, cash flow, and efficiency.
• Develop and maintain driver-based financial and operational models that connect budgets, targets, expected outcomes, decisions, and levers to P&L and cash - so the business can keep score and verify impact.
• Shape the analytical data foundation across finance, GTM, and the customer lifecycle - partnering with internal systems/data resources and cross-functional teams to structure, reconcile, and transform data from multiple systems into reliable inputs for models, reporting, insights, and decision support.
• Partner cross-functionally to translate company priorities into measurable goals, roadmaps, and operating actions - working directly with finance and operations leaders to influence change and track progress.
• Build the business intelligence and reporting layer that gives leadership a clearer, faster view of performance outcomes - ARR growth, cash management, profitability, and unit economics.
• Build repeatable processes that turn inputs from different teams and systems into clear outputs leaders can use, with defined owners, handoffs, timelines, and follow-through.
• Use modern tools, automation, and AI where practical to reduce manual work, improve analysis, and surface efficiency opportunities.

Business Analyst, Strategic Finance – Enterprise Analytics

• Develop and implement annual QDA business plans
• Monitor industry developments to ensure team access to best-in-class capabilities
• Collaborate with all PCR solution teams for successful project delivery
• Manage staff, including interviewing, job description preparation, and performance management
• Drive thought leadership for continuous scientific improvement
• Oversee qualitative components of PCR studies, including data management and analysis
• Manage qualitative research technologies for data collection and analysis

Senior Director, Qualitative Data Collection and Analysis

• Ensures data is accurate, complete, and fit for performing data analyses through various testing procedures and data controls
• Develops and executes on Enterprise Data Management policies and standards
• Manages data related incidents and identifies, communicates, and resolves or escalates issues as needed
• Develops, manages, and executes on controls, ensuring tracking, monitoring, and resolution of any control breaches with data platform
• Partners with Business and Technology functions to drive the development of business and functional requirements documents

Senior Data Analyst – Securities Reference Data

• 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 lead the end-to-end people analytics strategy aligned to HR & Community and business priorities.
• Deliver actionable insights that inform workforce, talent, and business decisions.
• Translate complex data into clear, compelling narratives for executive leaders.
• Advance analytics capabilities from descriptive reporting to predictive and forward-looking insights.
• Develop scenario modeling and forecasting capabilities to anticipate future workforce needs.
• Define and execute the HR&C data strategy to support scalable analytics, reporting, and AI use cases.
• Ensure data structures, quality, and accessibility support advanced analytics and AI adoption.
• Partner with product and technology teams to enable data-driven and AI-enabled HR&C solutions.
• Represent the HR&C domain in enterprise data governance, ensuring alignment with data standards and controls.
• Lead a high-performing, multidisciplinary team spanning analytics, data strategy, and research.

Head of People Analytics – Data

• Develop a deep understanding of GSK’s Vaccine & AIR therapeutic area
• Lead insight-generating analytics
• Partner with other functional areas in Medical Analytics
• Synthesize findings from various sources into actionable customer insights
• Champion insight approaches, frameworks, and analytic methods

Manager, Medical Analytics Insights – Vaccines/Anti-Infectives & Respiratory

• Own the operating model for approved analytics platform access across Excel, Python, Java, databases, APIs, and related application layers.
• Define and maintain standards for access patterns, version control, entitlements, testing, documentation, support procedures, and production evidence.
• Partner with quantitative developers and technology teams to deliver stable, reusable, performant, and controlled analytics interfaces.
• Support release management and regression testing for analytics platform changes, including API updates, calculation changes, interface changes, downstream impacts, defect review, certification, and rollback planning.
• Lead productionalization of high-value or high-risk Excel-based analytical tools, including standardized inputs, outputs, data sourcing, calculation sequencing, ownership, documentation, and controls.
• Support performance monitoring and remediation across Excel, Python, Java, database, batch, and application-based workflows.
• Help define database interaction patterns for market data retrieval, reference data, static data, output persistence, audit trails, usage monitoring, and downstream consumption.
• Support controls around curve creation, curve storage, curve publishing, overrides, version references, restricted data, and controlled database-consumed outputs.
• Use AI-assisted tooling where appropriate to improve documentation, test-case generation, regression analysis, exception detection, support workflows, and platform knowledge management.
• Serve as a coordination point across quantitative model owners, technology partners, business users, risk stakeholders, and support teams.

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