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

• 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

• 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

• Assists in development and analysis of quantitative/econometric behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning.
• Supports more experienced analysts and management in data analysis, model development efforts and ad-hoc analysis as needed.
• Assist in researching and developing quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning, including but not limited to, loan delinquency, default and loss models, loan prepayment and utilization models, deposit attrition models and financial instrument valuation methods.
• Prepare, manage and analyze large customer loans and deposit data sets for statistical analysis in Structured Query Language (SQL) or similar tool to properly specify and estimate econometric models to understand customer or Bank behavior for purposes of interest rate, liquidity or stressed capital risk.
• Understand the context of the Bank's data and businesses to ensure properly developed models.
• Produce and run regressions (including time series and logistic regression), programming routines and other econometric analyses to specify models using appropriate statistical software; communicate results, including graphic and tabular forms of model development activities to fellow team members, Treasury management and Bank-wide stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
• Execute models in production environment; communicate analytical results to Bank-wide stakeholders.
• Track portfolio performance, model performance, campaign tracking and risk strategy results.
• Incorporate observations and data into existing models to improve predictive results.
• Identify deviations from forecast/expectations and explain variances.
• Identify risk and/or opportunities.
• Support development and maintenance of satisfactory model documentation, including process procedures and performance monitoring guidelines to serve as reference source.
• Provide financial analysis and data support to other groups/departments across the Bank as required.
• Engage with colleagues in Model Risk Management for model validation exercises.

Credit Model Development Quantitative Analyst I – HELOC, Residential Mortgage

• 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

• Data analysis/guided deliverable development in support of assessment/strategic deliverables
• Develop project plan; manage the day-to-day tasks; and meet project deadlines
• Work effectively across teams to ensure client satisfaction
• Contribute to innovation, process improvement, standardization - Deliver high quality analytical solutions on-time

Lead Analyst, Customer Analytics

• Support a CDC public health evaluation initiative
• Analyze and evaluate public health activities
• Provide expert advice and consultation
• Communicate findings and recommendations clearly
• Collaborate with high-level officials and community members

• Support one or more analytical aspects of the business products and services life cycle
• Work with more senior team members, customers, Data Engineers, Data Architects, and Capability Managers to capture capability needs and drive quality data and reporting solutions
• Create and maintain deliverables such as data set creation, operational reports, and analytical dashboards
• Collaborate with cross-functional teams on data-driven projects
• Conduct requirement walkthroughs and sprint reviews
• Assure compliance for required standards and all necessary approvals have been obtained throughout the data delivery lifecycle

Associate Data Solutions Analyst

• The Litigation Data Analyst – Mass Tort & Product Liability serves as a strategic insights partner to our premier mass tort and product liability practice.
• This position will leverage data analytics to guide litigation strategy, predict case outcomes, and optimize financial performance across complex multi-plaintiff litigation portfolios.
• Analyze historical verdict data, settlement patterns, and case characteristics to develop predictive models for case valuation and outcome probability
• Build comprehensive databases of comparable verdicts, settlements, and judicial decisions to support case strategy and client counseling
• Develop statistical models to assess likelihood of settlement versus trial outcomes based on case factors, jurisdiction, and opposing counsel profiles
• Create financial modeling frameworks to project settlement ranges, trial outcomes, and expected case values across different scenarios
• Monitor and analyze mass tort inventory performance, identifying trends in case development, settlement velocity, and financial outcomes
• Collaborate with litigation teams to understand case development challenges and translate them into analytical problems
• Structure complex litigation problems into clear analytical tasks, supporting strategic decision-making on case selection, resource allocation, and settlement timing
• Prioritize analyses based on case value, urgency, and strategic importance to the practice
• Design and build automated dashboards tracking key litigation metrics including case inventory, settlement rates, average case values, and practice profitability
• Create executive-level reports on practice performance, including revenue forecasts, cost analysis, and profit margins by case type and jurisdiction
• Streamline existing case reporting processes to ensure timely and accurate delivery of key performance indicators
• Present findings and recommendations in clear, concise manner tailored to different audiences (partners, associates, clients, experts)
• Clean, manipulate, and analyze large litigation datasets to extract trends, patterns, and actionable insights
• Use statistical and data modeling techniques to support litigation strategy and business development decisions
• Connect analytical findings to litigation strategy, financial outcomes, and client impact
• Partner with attorneys, paralegals, case managers, and finance teams to gather requirements and align on analytical objectives
• Collaborate with business development team to identify market opportunities and practice growth strategies
• Share knowledge and best practices with litigation teams to elevate analytical capabilities across the practice

Litigation Data Analyst – Mass Tort, Product Liability

• Work directly with Marketing, Sales, and CX leaders to diagnose business challenges, define analytical roadmaps, and drive growth strategies.
• Develop rigorous analyses, models, and frameworks to optimize customer acquisition, lifecycle engagement, and retention.
• Build scalable machine learning solutions (e.g., targeting, segmentation, uplift modeling, LTV prediction) that improve growth efficiency and ROI.
• Drive acquisition, retention, and monetization through data-driven experimentation and modeling.
• Translate complex data insights into clear, actionable recommendations that influence decision-making at all levels of the organization.
• Collaborate with engineering teams to productionize models and analytics pipelines with high reliability and performance.
• Familiar with state of art AI solutions in Data Science domain and mentor Jr. data scientists.
• Drive best practices in experimentation, measurement, and growth analytics across the company.

Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

• Manages the end-to-end lifecycle of critical talent programs: performance management (goal setting, mid-year, and year-end) and employee engagement
• Analyzes and translates people and business data into actionable insights and recommendations that drive talent, performance, culture, and employee engagement strategies
• Consults with team members to execute various surveys, programs, and plans across the business to measure and enhance performance and impact
• Collaborates on driving the rollout of career frameworks, talent reviews, succession planning, and development planning
• Creates executive-level talent presentations that transform complex information into compelling narratives, using advanced PowerPoint design, visualization, and storytelling techniques to effectively communicate insights and recommendations
• Supports the broader HR team with a variety of ad hoc performance, talent management/ analytics-related projects and/or initiatives to support business growth and people-related objectives.

Manager, Talent & People Analytics

• Consults with stakeholders to lead workstream scoping and prioritization through problem statement-oriented discovery and solutioning
• Transforms and maintains datasets for practical, scalable application
• Builds sophisticated statistical modeling to identify trends, evaluate causality and forecast results with viable outcomes
• Synthesizes results into succinct, easily digestible deliverables
• Delivers professional data products (e.g., dashboards, reports, documentation) with prescriptive, actionable insights
• Leverages automation tools to streamline data ingestion and outputs
• Leads continuous improvement of existing processes to refine, synthesize, and standardized workstreams
• Maintains documentation outlining key projects and processes
• Advocates for resource prioritization according to strategic demand and business value
• Promotes a healthy, professional work environment and culture reflecting M&T Bank’s brand

Lead Business Analytics, Reporting Analyst

• Define and execute the enterprise Data, Analytics, AI, and Automation strategy
• Develop and maintain a multi-year roadmap for data modernization
• Advise executive leadership on emerging technologies, AI trends, opportunities, and risks
• Manage enterprise data platform architecture, including the Enterprise Data Warehouse, Azure Data Lake
• Establish enterprise data governance, data quality, and master data management capabilities
• Develop enterprise analytics capabilities that improve decision-making
• Drive adoption of intelligent automation and AI capabilities to improve productivity
• Build, lead, and develop a high-performing organization

Senior Director, Enterprise Data, Analytics, AI & Automation

• Designs, develops, and maintains enterprise data analytics solutions, business intelligence dashboards, and Microsoft Power Platform applications that drive decision-making across manufacturing operations, engineering, finance, and executive leadership.
• Partners with cross-functional stakeholders to transform complex data into trusted, scalable, and user-friendly products by performing the following duties.
• Build, deploy, and maintain custom business applications using Microsoft Power Apps (canvas and/or model-driven) and automate workflows using Power Automate to streamline manufacturing and back-office processes.
• Develop and maintain semantic data models, dimensional structures, and reusable reporting layers that serve as the trusted source of truth across the organization.
• Partner with Engineering, Operations, Finance, and Product stakeholders to gather requirements, define KPIs, and deliver multi-workstream analytics solutions end to end.
• Write, optimize, and maintain complex SQL queries, stored procedures, and data extracts against enterprise data warehouses and cloud platforms (e.g., Snowflake, Azure SQL, Redshift, MySQL).

• Review industry literature and research publications and maintain a system to curate publications, competitive intelligence, and internal research/reports.
• Create landscape summaries on topics relevant to higher education and update with new data and publications on an ongoing basis.
• Use third-party platforms to extract and summarize market data on programs and populations.
• Support Product Marketing in providing data summaries for program reviews and investigating new programs or products.
• Conduct deep-dive ad hoc research on market and competitive trends.
• Build, maintain, and update data models of external data sources (e.g., IPEDS), using tools such as Microsoft Fabric/PowerBI.
• Create and maintain data Python data ingestion notebooks in BigQuery and Microsoft Fabric.
• Use existing data models to monitor and summarize internal performance trends across products, segments, and demographics.
• Build and enhance reports and dashboards according to feedback, insights, and institutional goals.
• Actively seek opportunities to improve and anticipate feedback on analytic projects and tools.
• Present analysis findings to diverse audiences in a variety of formats.
• Utilize project management software to keep track of multiple priorities and projects.
• Attendance, punctuality, and reliability are essential functions of this role.

Market Research Data Analyst

• Perform deep-dive analyses across diverse data sources to identify trends, patterns, and opportunities.
• Write and optimize custom SQL queries to extract, transform, and analyze data.
• Use advanced Excel techniques (pivot tables, formulas, data modeling) to explore and visualize findings.
• Create user-friendly Tableau reporting to illuminate critical business insights, analysis, and recommendations for senior stakeholders.
• Proactively identify gaps, anomalies, and emerging patterns that may impact business performance.
• Partner with cross-functional teams to support strategic and operational decision-making.

• Performs data analysis, and interpretation.
• Develops rules and methodologies for data collection and analysis.
• Work collaboratively within a team of data analysts and other MPIC staff to obtain data and analysis to support program work.
• Analyze and evaluate enrollment data related to consumer and Agent/Broker activity within the Marketplace.
• Safeguard PII and PHI

Data Analyst II

• Assist with collecting, organizing, and validating sales and customer data from CRM and other business systems.
• Support the creation and maintenance of reports and dashboards to track sales performance, pipeline activity, and key business metrics.
• Analyze trends and identify opportunities to improve data quality, reporting accuracy, and operational efficiency.
• Prepare summaries and visualizations to support business reviews and leadership decision-making.
• Partner with Sales, Marketing, Customer Success, and Revenue Operations teams on ad hoc projects and analyses.
• Document processes and recommend improvements to reporting and data management practices.

Summer Intern – Sales Operations Data Analyst

• Profile, cleanse, and reconcile outage notification data from email/PDF samples, carrier templates, RDS PostgreSQL tables, S3 landing zones, and exported operational datasets.
• Support AI extraction evaluation loops by comparing model output to human-labeled gold data across severity, notification type, service affected, service layer, root cause, lifecycle, carrier type, verification, and state/geography fields.
• Develop SQL queries, Python/pandas analysis scripts, and repeatable QA checks that measure extraction accuracy, completeness, timeliness, duplicates, alert eligibility, and carrier-level data quality.
• Build dashboard-ready datasets and reporting marts for executive dashboards, national heat maps, carrier scorecards, trend summaries, compliance reports, and crisis-center/state-coordinator operational views.
• Partner with the Data Architect on canonical data models, metric dictionaries, lineage notes, source-to-target mappings, row-level security rules, and dashboard acceptance criteria.
• Create and maintain QuickSight, Power BI, Tableau, or equivalent BI artifacts depending on the approved platform, including KPI definitions, filters, drilldowns, and test cases.
• Analyze grant lifecycle and federal operations data where needed, including eRA/PMS exports, SharePoint trackers, NOFO workflow data, SAM.gov/DNP verification outputs, and manually reconciled spreadsheets.
• Support UAT by preparing test data, validating dashboard numbers with stakeholders, triaging data defects, and translating user feedback into backlog-ready analytical requirements.
• Document repeatable runbooks for data validation, dashboard refreshes, exception handling, and production reporting operations.
• Contribute evidence and documentation for federal security, privacy, and ATO reviews, including audit trails, data handling assumptions, and data quality controls.

Data Analyst jobs in Maryland

See all jobs on JobTailor

Trauma Registrar, Data Analyst

Staff Product Manager, Data & Analytics

Collision Data Analyst

Data Analytics Co-Op

Credit Model Development Quantitative Analyst I – HELOC, Residential Mortgage

Online Data Analytics Eco Representative

Lead Analyst, Customer Analytics

Data Analyst

Associate Data Solutions Analyst

Litigation Data Analyst – Mass Tort, Product Liability

Lead Data Scientist – Property Catastrophe Modeling, Geo-Analytics

Manager, Talent & People Analytics

Lead Business Analytics, Reporting Analyst

Senior Director, Enterprise Data, Analytics, AI & Automation

Data Analyst

Market Research Data Analyst

Data Analyst

Data Analyst II

Summer Intern – Sales Operations Data Analyst

Data Analyst