Data Analyst

• Play a key role in helping Gravie to understand the performance of its business, understand new opportunities, and translate those insights into solutions that meaningfully improve the health benefits people get and the healthcare they receive.
• Ask and answer the right questions, including: How are we doing? What should we continue doing? What should we stop doing?  What should we start doing in the future?
• Take ownership of regular deliverables for various business units, leveraging multiple technologies to produce solutions that are consistent, accurate, and efficient.
• Assist in the design and execution of diverse quantitative and qualitative analyses to support the evaluation, management, and growth of new and existing products for areas across the business.
• Use analytic and communication skills to tell stories with data, transforming basic and complex datasets into clear, actionable insights for both technical and non-technical audiences to influence business decisions and product roadmaps.
• Support a culture of using data to inform decisions within the organization.
• Apply established quality assurance measures to ensure the accuracy, reliability, and consistency of all analytical deliverables.
• Contribute to the design, development, and enhancement of our growing analytics platform by partnering with cross-functional teams to effectively integrate data insights into business strategies and product improvements, in a robust and scalable fashion.
• Collaborate closely with other Analysts to share knowledge and best practices, fostering an environment of knowledge sharing and professional development.

• Partner with technology teams to design and deliver scalable data solutions that provide high-quality, reliable data for business use
• Drive adoption and business value from data, analytics, and BI solutions across functions
• Translate business needs into clear data and technology requirements
• Collaborate across business units to standardize and optimize enterprise data assets
• Support data governance and data quality initiatives in close partnership with Technology
• Act as a subject matter expert (SME) for business data inquiries
• Perform ad hoc analysis by extracting, transforming, and modeling data from multiple sources
• Validate and sign off on data deliverables to ensure accuracy, consistency, and adherence to standards
• Contribute to Agile delivery of data initiatives in partnership with Technology teams

Data Analyst – Data & Analytics

• Own the end-to-end process of extracting and compiling member lists from multiple internal data sources — eligibility systems, pharmacy data, client records, and more — for use across email, SMS, and print communications. Your primary workspace is Snowflake, querying across the data models maintained by our Data Engineering and Analytics teams.
• Define and enforce data quality standards across all member lists before they enter the delivery pipeline. Build and maintain automated checks that surface anomalies — duplicate records, missing fields, invalid formats, eligibility mismatches — before a single message is triggered.
• Handle Protected Health Information with the rigor and discipline it demands. Own suppression list logic, ensuring members who have opted out, are ineligible, or fall under regulatory exclusions are accurately reflected across all lists at all times. Treat opt-out, preference, and PHI data as the highest-priority data in the pipeline.
• Work hand-in-hand with the Marketing Operations Manager to ensure lists are formatted, mapped, and structured exactly to the schema required by communication platforms. Maintain an active working relationship with the centralized Data team — contributing to shared data models and quality standards, staying aligned on upstream changes, and advocating for member communications data needs at the infrastructure level.
• Extract, transform, and validate member data from multiple internal systems using Snowflake, producing clean, audit-ready lists for every communication send
• Build and maintain automated data validation workflows that catch quality issues — gaps, duplicates, mismatched fields, ineligible members — before lists are handed to Marketing Operations
• Own suppression and exclusion logic, including regulatory opt-outs, eligibility exclusions, and client-specific rules, and ensure they are consistently applied across all channels and send types
• Partner closely with the Marketing Operations Manager on list specifications, field mapping requirements, and pre-send data checks — you are the upstream dependency for every campaign they deploy
• Maintain clear documentation of data sources, transformation logic, field definitions, and business rules to support auditability and regulatory compliance
• Collaborate with the centralized Data team to stay aligned on Snowflake data model changes, contribute to shared data quality standards, and represent member communications requirements in data infrastructure decisions
• Proactively identify, escalate, and root-cause data quality issues, partnering with the Member Comms Team Lead and internal data owners to drive resolution
• Support ad-hoc data pulls for compliance reporting, campaign sizing, program performance analysis, and regulatory inquiries

Marketing 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.

• Analyzing structured and unstructured data from MESH and integrated CMS systems (MBES, MacFin, T-MSIS, SPoTT, CMCS DataConnect) to surface insights about state Medicaid program funding, performance, compliance, and modernization
• Designing, building, and maintaining interactive dashboards and reports in Power BI and Salesforce reports/dashboards that consolidate financial, operational, certification, and compliance data into a single workspace for CMS reviewers and leadership
• Supporting Master Detailed Budget Table (MDBT) modernization by reconciling and validating historical and current MDBT data, including line-item mapping across legacy and current formats and verification of total computable, state-share, and federal-share calculations
• Profiling and validating data ingested from spreadsheets (Excel, CSV), documents (PDF, Word), APIs, and enterprise datasets to ensure accuracy, completeness, and alignment with CMS data-governance standards
• Translating CMS reviewer and leadership questions into well-defined analytic requirements, data queries, and visualizations; iteratively refining outputs based on stakeholder feedback
• Documenting data lineage, business definitions, calculation logic, and dashboard methodology in the MESH knowledge base and Confluence to support transparency and auditability
• Partnering with engineering to define data-quality rules, anomaly detection criteria, and automated reconciliation logic that flag funding decreases, mismatched FFP rates, and other discrepancies
• Producing ad-hoc data extracts, briefings, and analyses for CMS leadership in support of Congressional inquiries, audits, briefings, and policy decisions, often on short turnaround
• Supporting Section 508 compliance for all dashboards, reports, and visualizations including color-contrast, alternative text, and assistive-technology compatibility
• Collaborating with the AI/ML team to validate AI-generated submission analysis outputs, monitor model drift, and confirm explainability of recommendations presented to CMS reviewers
• Participating in agile ceremonies, contributing user stories and acceptance criteria for analytics and reporting features, and demonstrating completed work to CMS Product Owners
• Maintaining clear, current documentation of dashboards, KPIs, and methodologies to enable hand-off and continuity in line with CMS transition requirements

• Partner with key stakeholders to define success and develop measurement frameworks
• Dive deep into complex business problems and provide insights on merch performance through hypothesis testing
• Responsible for delivering a suite of analytical products include analyses, dashboards, insights, and recommendations
• Present the results to the stakeholders up to executive level and guide them to make the best use of analytics in their domain
• Own the definition and implementation of new metrics
• Find opportunities to use data to develop new strategies and improve overall performance
• Deliver high quality solutions and recommendations to a variety of problems both independently and through the collaboration with team members and business partners
• Bring data to life through storytelling in a clear and meaningful way to audiences with mixed levels of technical expertise
• Reconcile divergent demands from multiple stakeholders in a fast-paced work environment
• Mentor more junior team members on analytics, storytelling and communication best practices
• Influence and support the Center of Excellence standards and best practices of analytics
• Use advanced analytical and statistical practices to create thorough and actionable insights

Data Analyst 3, Merchandising Customer Insights

• Support the Data Center of Excellence (Data COE) team across five key areas: documentation of data processes and reporting logic, exploratory data analysis beyond standard grant reporting, data pipeline and dashboard cleanup and maintenance, qualitative data capture from member research and surveys, and general research to support grant strategy and benchmarking.
• Draft and refine plain-language documentation of how metrics are calculated, data is cleaned, and reports are generated for grant programs.
• Develop step-by-step guides for updating and maintaining Power BI dashboards and grant reporting processes.
• Perform exploratory analysis on grant data (e.g., credential and placement outcomes, wage trends, training impact) and prepare summary findings for the team.
• Assist with data quality checks, including identifying duplicates, missing values, and inconsistencies across datasets.
• Support data pipeline tasks such as validating outputs, documenting code logic, and assisting with light cleanup of Python notebooks.
• Synthesize qualitative feedback and patterns from member meetings, surveys, and program interactions into structured summaries.
• Conduct landscape research on how peer organizations handle subgrantee data reporting, metric definitions, and data collection practices.
• Support preparation of materials for internal and external stakeholder meetings as needed.

Intern, Data Analytics – Mission Data & Grants

• Develop and maintain a variety of dashboards, scorecards, and reporting tools (standard, ongoing, ad-hoc) that deliver real-time insights and data visualization on staffing trends, demand forecasting and operational performance
• Manage SimpliFi's survey and evaluation data for all performance and assignment completion evaluations across clients
• Develop and implement a data management strategy to ensure data accuracy, accessibility, relevance, and consistency across systems
• Develop, maintain, and manage a robust menu of scheduled reporting and analysis to inform business decision-making
• Work closely with Operations and Client Strategy to develop analytics tools that align with business objectives; apply industry knowledge to interpret data and improve performance
• Develop, implement, and maintain a system for keeping data/reporting SOPs current
• Lead and/or participate in data and analytics projects by executing the entire data analytics life cycle (e.g., including meeting with business stakeholder, gathering requirements/discovery, data preparation/cleaning, building reports visualizations, communicating results, operationalization)
• Continually explore and implement ways to improve/streamline current data gathering and reporting processes for maximum efficiency and scalability
• Serve as an advisory resource for other team members by providing guidance and assistance on data and analytics-related interactions

Manager, Ops Data Analytics

• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality
• Acquire data from primary or secondary data sources and maintain databases/data systems
• Identify, analyze, and interpret trends or patterns in complex data sets
• Proactively create reports and graphs that may be useful and provide insights resulting from various experiments
• Work closely with management and IT team to prioritize business and information needs
• Import, clean, transform, validate or model data with the purpose of understanding or making conclusions from the data for decision making purposes
• Use statistical tools to improve data quality and for designing or presenting conclusions gained from analyzing data
• Work with IT team colleagues to extract data relevant for analysis; Create data definitions for new database file/table development and/or changes to existing ones as needed for analysis
• Collaborate with IT colleagues, Administration associates, and upper management to integrate data mining results with existing and new reports
• Work on multiple projects simultaneously

Data Analysis Associate

• Supports the extraction of data using a variety of programming languages, such as SQL, SAS, Python, or Spark/Scala
• Connects provisioned data across multiple sources and performs necessary transformations utilizing both technical, business, and process knowledge to transform data into meaningful values and insights
• Performs quantitative techniques and analysis on customer, transaction, and performance data
• Follows requirements developed by other analysts and supervisors to perform required research, analytics, and exploration on appropriate and accurate data sources
• Communicates complex subjects in a simple and engaging manner to non-technical and technical business partners using software such as Power Point, Word, Excel, and Tableau
• Assists with conducting quality comparison checks on analysis output and escalates data inconsistencies, gaps, or issues to leadership

Client Quantitative Analyst I – Analytics Transformation

• Conduct exploratory data analysis and develop dashboards
• Engage with cross-functional teams to understand data requirements
• Ensure accuracy of visualizations through quality assurance
• Design and implement data ingestion pipelines
• Monitor pipeline health and dashboard performance

Contract Data Analyst

• Develop, iterate, and maintain comprehensive reports and automated dashboards using visualization platforms
• Analyze the end-to-end user journey
• Partner with growth and commercial teams to track performance and scale B2B initiatives
• Support the lifecycle marketing team by tracking engagement metrics and campaign performance
• Work closely with your mentor to upskill and transition into a senior role

Data Analyst, Growth

• Build a cohesive view of Harvey's employee lifecycle — connecting recruiting, onboarding, engagement, performance, mobility, retention, and exits into a single, actionable narrative that shows where exceptional talent thrives or breaks down
• Own the vision and roadmap for Harvey's people data infrastructure — partner with Data Engineering and Security to stand up the people data layer in Snowflake (or similar), define architecture requirements, and drive role-based access controls and data governance so the right people have the right access
• Consolidate workforce data across Workday, Ashby, Envoy, Culture Amp, and other HR systems, and build the data quality frameworks that keep it trustworthy at scale
• Define and maintain Harvey's people metrics dictionary — standardize how headcount, attrition, hiring, and workforce trends are measured across the org
• Design the frameworks and methodologies that scale beyond v1 — forecast headcount, model attrition, segment the org, benchmark against market — built to explain not just *what* is happening but *why*
• Move People Analytics beyond reporting into intervention — surface leading indicators, manager behaviors, operational friction, and emerging org risks before they become scaled people problems, and help Harvey understand what attracts, enables, retains, and risks losing exceptional talent
• Build dashboards that give leadership clear visibility into the workforce, cuttable by org, region, and function — and shape exec-level decisions with the insights they surface
• Build the self-service foundation that lets partner teams operate independently — design the frameworks, tooling, and documentation so that comp, PBPs, and other partners can surface their own insights without routing every question through analytics
• Drive alignment across PBPs, RecOps, People Systems, and Finance to define reporting cadence and answer the questions that drive strategic people decisions
• Set the bar for people data craft at Harvey — define standards, review work, and grow the analytics capability of partner teams
• Use AI aggressively to automate workflows, accelerate analysis, and scale your impact — this is a role where AI-first thinking compounds fast

People Data Analytics Lead

• Guide and mentor the team in best practices for handling the data.
• Review and provide feedback before the deliverables are shared with the customer.
• Play with and transform data.
• Work towards creating easy-to-digest analytical reports for US healthcare customers.
• Design and build workflows on the Data Activation Platform that pull data from client systems as scoped while complying with respective internal standards and industry best practices.
• Review team deliverables and ensure quality and accuracy.
• Monitor and tune the configuration of workflows for high availability once deployed in production environments.
• Understand Innovaccer data warehousing concepts and implement best practices.

• Own the end-to-end delivery of audience segmentation requests from Demand Generation teams
• Manage intake through Workfront, scoping requirements
• Build audience segments in Treasure Data and activate to downstream channels
• Manage the active request queue, maintaining delivery against agreed timelines
• Build audience segments directly in Treasure Data CDP, applying sound segmentation logic
• Develop working knowledge of the CDP data structure
• Work with AI-assisted audience generation via Treasure Data Audience Agent
• Apply consistent quality checks to all audience outputs
• Identify and escalate data quality issues within the CDP
• Maintain thorough documentation of segment definitions and QA outcomes
• Communicate with Demand Generation teams on requirements and any data constraints

Customer Data Analyst

• Lead the oversight, design, governance, and continuous enhancement of CRA data collection and systems management framework
• Partner with cross-functional teams to execute concurrent initiatives
• Drive organizational change to streamline data collection and ingestion through automation
• Perform ongoing analysis of CRA data, systems, and processes
• Provide compliance guidance to management based on CRA requirements and regulatory developments
• Serve as a systems subject matter expert for the bank’s CRA technology platform
• Identify and implement solutions to improve efficiency
• Update CRA data collection and systems frameworks to address change
• Manage system extract logic and data processing
• Partner closely with Enterprise Technology to define requirements
• Support internal audits, regulatory examinations, and compliance activities
• Independently manage and execute complex initiatives that enhance data ingestion

CRA Compliance Systems and Data Analyst

• Support the Batch Reprocessing and Payment Integrity function by designing and delivering the reporting, dashboards, and analytical tooling that measure operational performance across the claims reprocessing lifecycle.
• Partner with operations leadership to define complex reporting requirements.
• Build repeatable and auditable data pulls in place of manual one-off extracts.
• Contribute to data quality and stewardship.
• Design, build, and maintain operational dashboards and reports that track reprocessing cycle time, post-approval turnaround, queue and hold status, stalled or aging tickets, contestment volume, and recovery throughput.
• Write and optimize complex SQL against multiple claims adjudication systems and an enterprise data platform.
• Replace manual, ad-hoc extracts with documented, repeatable, and parameterized data pulls.
• Translate operational questions from team leadership into clear reporting requirements.
• Conduct ad-hoc analysis to answer time-sensitive operational and prioritization questions.
• Support data quality and stewardship efforts.

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