Role Description Our client is building a brand-new analytics team within their Ambulatory division and is seeking a driven Data Analyst to help shape how referral and provider data is used to improve patient access, care continuity, and growth. This role partners closely with Physician Relationship Managers, operations leaders, and analytics teams to transform referral, claims, and EHR data into actionable insights that drive measurable impact. Key Responsibilities - Data Management & Governance - Manage and enhance referral and provider data feeds across multiple systems - Combine, cleanse, and validate data from sources such as Epic (EHR) and claims systems - Partner with IT and enterprise analytics teams to ensure data integrity and usability - Build consistent, governed datasets to support dashboards and reporting - Analytics & Insights - Analyze referral patterns, care continuity, and provider performance trends - Identify out-of-network leakage and gaps in care continuity - Develop provider segmentation and targeting strategies - Translate findings into clear, executive-level insights and recommendations - Identify breakdowns in referral-to-encounter workflows and escalate opportunities for improvement - Reporting & Visualization - Design, build, and maintain Power BI dashboards focused on referral performance - Deliver ongoing and ad hoc reports (e.g., referral conversion, share of care, in-network utilization) - Track and measure outcomes of interventions over time - CRM & Process Optimization - Maintain CRM data structure, reporting integrity, and documentation standards - Train internal users on CRM best practices and ensure consistent data entry - Support initiatives to improve referral workflows and provider engagement - Cross-Functional Collaboration - Partner with Ambulatory, Acute, Access, and Service Line leadership - Serve as a liaison between business teams and enterprise analytics - Assist in onboarding providers to electronic referral tools - Support development of standardized playbooks and growth strategies Qualifications - 3–5 years of data analysis experience in a healthcare environment - Strong experience working with Epic referral data and workflows - Hands-on expertise with Power BI dashboards (required) - Advanced proficiency in Excel - Deep understanding of the referral lifecycle (entry → processing → outcomes) - Experience integrating and analyzing data from multiple systems Preferred Qualifications - Experience with claims data and healthcare performance metrics - Familiarity with CRM tools and data governance best practices - Understanding of hospital billing or ambulatory operations - Strong project management and communication skills What We’re Looking For - Analytical, strategic thinker with a “go-getter” mindset - Strong communicator who can translate data into actionable insights - Ability to work cross-functionally and influence stakeholders - Comfortable in a fast-paced environment building processes from the ground up Work Environment - Fully remote - Must reside in one of the following states: AL, DE, FL, GA, IN, KS, LA, ME, MD, MN, NE, NH, NC, ND, OH, OK, PA, SC, SD, TN, TX, UT, VA, WA, WV, WI, WY Interview Process - 2 steps, both virtual Additional Details - Contract-to-hire opportunity - Must be able to pass additional drug, personal history, employment screenings upon hiring Job Type & Location - This is a Contract to Hire position based out of Norfolk, VA. Pay and Benefits - The pay range for this position is $45.00 - $55.00/hr. - Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. - Benefits are subject to change and may be subject to specific elections, plan, or program terms. - If eligible, the benefits available for this temporary role may include the following: - Medical, dental & vision - Critical Illness, Accident, and Hospital - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available - Life Insurance (Voluntary Life & AD&D for the employee and dependents) - Short and long-term disability - Health Spending Account (HSA) - Transportation benefits - Employee Assistance Program - Time Off/Leave (PTO, Vacation or Sick Leave) Application Deadline - This position is anticipated to close on Jul 11, 2026.

Role Description Client is looking for Senior Business Analyst to support Data Democratization initiatives, and this is a remote position working with US CST Hours. - Work with business stakeholders to elicit, analyze, and document data, reporting, and analytics requirements across multiple business domains. - Analyze existing reports, dashboards, and datasets to identify gaps, redundancies, data quality issues, and opportunities for standardization or decommissioning. - Translate business requirements into well-defined user stories and acceptance criteria in Azure DevOps. - Partner closely with Data Engineers and Data Analysts to ensure business requirements are correctly implemented in data pipelines, semantic models, and reporting layers. - Support data validation and reconciliation activities by reviewing source-to-target mappings and business rules. - Coordinate and support User Acceptance Testing (UAT), ensuring stakeholder validation and approval prior to production deployment. - Document business definitions, KPIs, and data logic used in downstream reporting and analytics solutions. - Participate in Agile ceremonies including backlog refinement, sprint planning, reviews, and retrospectives. - As part of the Data Products team, help deliver accurate, complete, and timely data products that meet business needs. - Support initiatives related to Data Democratization, including self-service analytics enablement and data literacy efforts. - Deliver on predefined individual and team goals with a focus on quality and stakeholder satisfaction. Qualifications - 5+ years' experience working in enterprise data, reporting, analytics, or business analyst roles. - Experience in Data Analysis for Data & Reporting products. - Strong hands-on data analysis skills using Python, SQL, Databricks, and Power BI. - Strong quantitative, analytical, and interpretive skills. - Experience with Oracle, Salesforce data schemas; ability to map data flows from source systems to Databricks. - Practical experience working in Agile/Scrum environments. - Ability to multi-task and work in a team environment, while following a flexible schedule to meet deadlines. - Able to present clearly and persuasively, listen and solicit clarification, and respond articulately to questions. - Follows policies and procedures and supports the organization's goals and values. - Can coordinate multiple parallel initiatives, communicate changes and progress, and complete deliverables on time and within budget. - Ability to interpret a variety of instructions furnished in mathematical, written, oral, diagram, or schedule form. - Working knowledge of Databricks/Snowflake administration/architecture and capabilities. - Ability to query and display large datasets while maximizing the performance of the workbook. - Ability to interpret technical or dashboard structure and translate complex business requirements to technical specifications. - Work with business stakeholders to create valuable reports and dashboards that provide insight, improve/automate processes, or add value to the team. - High-level competency in Excel (Vlookup, pivot tables, etc.). - Understanding of advanced calculations and statistical functions. - A solid understanding of SQL, relational database management systems, data modeling, and normalization. - Strong communication skills and attention to detail and accuracy. - Prior experience in Data Engineering and/or Data Science. - Familiarity or experience with Atlan and/or Sigma Computing tools is a plus.

Role Description The S4+ Data & Analytics Lead is the single-thread accountable leader for the end-to-end data and analytics agenda across the S4+ programme, owning all programme data outcomes across design, build, test, migration, cutover, and post go-live stabilisation. - Ensures the programme delivers clean, reconciled data, trusted analytics, and AI ready foundations. - Protects operational and financial integrity through cutover. - Defines standards and chairs programme data governance. - Stops or escalates delivery where data readiness or risk would compromise go-live integrity or future value realisation. - Ensures programme artefacts, controls, and ways-of-working become BAU-ready and are transitioned into business-as-usual operating rhythms post go-live. Key Responsibilities - Programme Data Leadership & Governance: - Single accountable owner for S4+ data outcomes; owns integrated data roadmap and governance. - Measures / Indicators: - Integrated data roadmap published, maintained, and used in programme governance. - Cross-domain dependencies and data risks tracked early and resolved through governance. - Information Modelling & Design Authority: - Own programme information modelling outputs and chair data-related design authority decisions. - Measures / Indicators: - Source-of-record (SoR) and information model artefacts approved and adopted. - Design authority decisions are evidence-based and minimise semantic divergence. - Migration, Readiness & Cutover Integrity: - Own end-to-end data migration and go live readiness; stop/escalate where data risk exists. - Measures / Indicators: - Evidence-based data gates achieved for readiness-to-test, readiness-to-cutover, and go-live. - Go-live recommendations supported by auditable evidence packs (reconciliation, defect position, residual risk). - Analytics & AI Enablement: - Deliver trusted analytics and AI ready foundations aligned to enterprise controls. - Measures / Indicators: - Trusted analytics maintained through cutover (one version of truth, agreed KPIs, lineage). - AI enablement criteria embedded into data gates and BAU-ready monitoring. - Decision Rights & Escalation: - S4+ Data & Analytics Lead — Decides: - Programme data standards and evidence requirements for data gates (within enterprise guardrails). - Data readiness go/no-go recommendations for each major gate, based on auditable evidence and residual risk. - S4+ Data & Analytics Lead — Stops / Escalates: - Stops or escalates delivery where data readiness threatens operational/financial integrity through cutover. - S4+ Data & Analytics Lead — Recommends: - Material risk recommendations to Exec/Board governance via the Data & AI Transformation Director, supported by evidence packs and mitigations. Key Outputs & Deliverables - Integrated S4+ Data Roadmap (including data gates, dependency map, and readiness milestones). - Programme Information Model Pack (SoR decisions, object catalogue, data quality rules, KPI definitions and lineage). - Migration & Cutover Evidence Packs (auditable reconciliation results, defect logs, residual risk dossier, go/no-go recommendations). - Trusted Analytics Pack (one version of truth KPI catalogue, lineage, reporting transition plan). - BAU Transition Pack (governance cadence, monitoring dashboards, ownership/stewardship model, early-life support routines). Job Knowledge/Education and Qualifications - Knowledge: - Data governance, migration, analytics and AI enablement in SAP S/4HANA programmes. - Information modelling artefacts (SoR, object catalogue, DQ rules, KPI lineage). - Data readiness and cutover integrity in ERP transformations. - Skills: - Programme leadership and delivery management. - Standard setting and enforcement across partners and domains. - Confident escalation where data risk threatens go live. - Capability: - Single thread accountability for S4+ data outcomes. - Establish and run programme data governance and design authority. - Protect operational and financial integrity through cutover. - Experience: - Leading data and analytics on SAP S/4HANA or ERP scale transformations. - Hands-on data migration, reconciliation and go live readiness. - Delivering trusted analytics and eliminating fragmented reporting. Benefits - Be part of a global organization dedicated to building a better future. - An opportunity to grow your own way with support and freedom to tailor-make your career. - Feel empowered to be yourself and belong in a welcoming, inclusive workplace.

• Perform advanced financial analysis and reporting to support strategic decision-making • Develop and maintain sophisticated financial models for cash forecasting, capital planning, treasury management • Conduct benchmarking, KPI analysis, and variance reporting to identify trends, risks, and opportunities • Oversee budgeting processes, cost accounting, and productivity standards; provide recommendations for process improvements • Mentor accounting staff, provide financial systems training, and support professional development within the finance team • Present complex financial information and recommendations to senior leadership