• Maintains awareness of the pertinent elements of contract and scope of work for assigned project(s) • Reviews and adheres to the requirements of study-specific Clinical Data Management Plans • Creates and enters test data for User Acceptance Testing (UAT) • Performs User Acceptance Testing (UAT) for data entry screens, edits and data review listings • Receives and enters lab normal ranges • Completes and submits Clinical Database Management System (CDMS)-specific access forms and/or spreadsheets • Performs reviews of discrepancy (edit check) output and validation listings based on data entered into the clinical database • Resolves answered queries and requeries where appropriate • For paper studies, takes receipt of, and reviews, Data Clarification Forms (DCFs) • Submits copies of the DCFs to sponsors as necessary • For paper studies, performs internal QC checks via listing output from database against CRFs and DCFs • For EDC studies, performs DM quality review and/or other internal QC checks as required per applicable electronic data capture (EDC) systems • Participates in internal meetings and internal/external audits as required • Maintains proficiency in Data Management systems and processes through regular trainings • Performs SAS mapping QC whereby discrepancies are noted on the SAS mapping test logs • Coordinates the work of CDAs assigned to the project • Provides training on data management activities and systems • Completes tasks within timeframe by appropriately prioritizing multiple tasks within or across projects • Runs data cleaning and/or status reports

• Drive encounter data quality, compliance, and operational performance. • Lead a team of 2–5 associates overseeing Medicare and Medicaid encounter data operations. • Identify and implement process improvements to increase efficiency, quality, and compliance. • Serve as a subject matter expert for Medicare and Medicaid encounter error correction processes. • Present performance results, key accomplishments, and areas of concern to business stakeholders.

• Define and govern metadata (data definition & structure) across workflows, automation, and AI-driven processes to ensure consistent, controlled system behavior • Establish standards for system configuration design, reuse, and lifecycle management across Salesforce and integrated platforms • Lead end-to-end data conversion as a business function—not just a technical activity • Partner with regions to drive data assessment, profiling, cleansing, and enrichment • Own object mapping from legacy systems to Salesforce and downstream platforms, ensuring decisions support operational continuity, auditability, and reporting integrity • Own the end-to-end governance of system configuration changes, including intake, prioritization, impact assessment, and release management • Establish full traceability of metadata changes, ensuring who changed what, when, and why is always visible • Govern AI agents (e.g., Agentforce) to ensure their actions are predictable, explainable, and aligned with business rules • Provide governance over data conversion activities, ensuring alignment between metadata structures, data models, and migration logic • Serve as the governance counterpart to IT and platform teams

• Manage and maintain Airtable databases to a high standard of data cleanliness and accuracy; • Track incoming support requests and collaborate with team members across Vocal departments to support a wide variety of data needs and deliver solutions; • Create and maintain scripts to automate data entry and ingestion; • Implement quality assurance protocols to ensure accuracy of data and technical products; • Assist with cleaning, preparing, and exploring data to support client reports and internal and external dashboards.