Manager, Program Research

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    "description_html": "<p>&nbsp;<strong>The Why Behind Wellvana:</strong></p><p>The healthcare system isn’t designed for health. We’re designed to change that. We’re Wellvana, and we help doctors deliver life-changing healthcare. &nbsp;</p><p><br>Through our elevated value-based care programs, we’re revitalizing an antiquated system that’s far too long relied on misaligned incentives that reward quantity of care not the quality of it.&nbsp;</p><p><br>Our enlightened approach—covering everything from care coordination to clinical documentation education to marketing— ties the healthy outcomes of patients directly to shared savings for primary care providers, health systems and payors. &nbsp;</p><p><br>Providers in our curated network keep their independence, reduce their administrative headaches, and spend more time with patients. Patients, in turn, get an elevated experience with coordinated care between appointments that is nothing short of life-changing. &nbsp;</p><p><br>Named a 2024 \"Best in Business\" and 2023 \"Best Place to Work\" by Nashville Business Journal, we’re one of the fastest-growing healthcare companies in America because what we do works. This is the way medicine is meant to be.</p><p><br><strong>Clarity on the Role:</strong></p><p>The Manager of Program Research is an analytically driven individual contributor who applies deep expertise in Medicare claims data and health economics modeling to one of the most consequential analytical challenges in ACO management: ensuring that Wellvana's measured performance reflects the reality of care delivered.&nbsp;</p><p><br>Program Intelligence is Wellvana's function for identifying, analyzing, and responding to external claims behaviors, eligibility events, and utilization patterns that distort the ACO's benchmark, attributed population, or cost performance. This is a proactive analytical surveillance function at the intersection of claims data science, health economics, and value-based care program knowledge.&nbsp;</p><p><br>You will own the full analytical lifecycle: designing surveillance logic, investigating flagged patterns, building financial impact models, and producing outputs that protect ACO shared savings. You operate with high autonomy as the primary analytical engine of the team. Program knowledge will be developed in role — what you bring is the analytical foundation that makes that learning fast and durable.&nbsp;</p><p><br></p><p><br><strong>What's Expected:</strong></p><p><br></p><p><em>Claims-based surveillance &amp; pattern detection&nbsp;</em></p><ul><li>Design, build, and maintain surveillance logic against Medicare claims data to detect external patterns affecting ACO benchmark, attribution, and cost calculations — including eligibility enrollment events, provider billing anomalies, and post-acute utilization patterns.&nbsp;</li><li>Develop and refine statistical thresholds and decision rules distinguishing meaningful signals from expected variation; identify emerging pattern types and build detection logic independently.&nbsp;</li><li>Manage surveillance data feeds — CMS claims refreshes, provider taxonomy data, eligibility events, post-acute episode chains — including quality monitoring and refresh cadence oversight.&nbsp;</li></ul><p><em>Investigation &amp; financial impact modeling&nbsp;</em></p><ul><li>Review flagged patterns, apply documented decision rules to distinguish actionable signals from noise, and document findings — data sources, logic, disposition rationale — at the point of detection.&nbsp;</li><li>Build and maintain benchmark adjustment models quantifying financial impact on ACO shared savings position, including scenario ranges, documented assumptions, and sensitivity analysis.&nbsp;</li><li>Apply health economics methods — cost decomposition, risk adjustment analysis, utilization trending, population segmentation — to translate claims patterns into quantified financial findings with a complete longitudinal evidentiary record.&nbsp;</li></ul><p><em>Output development &amp; stakeholder delivery&nbsp;</em></p><ul><li>Develop and deliver operational flags to care management and network teams formatted for direct workflow integration; produce quarterly financial impact summaries for finance and program leadership with narrative context non-technical stakeholders can act on.&nbsp;</li><li>Build audit-ready analytical packages supporting program-level decisions and, in collaboration with the department leader and legal, CMS submissions.&nbsp;</li><li>Serve as a direct analytical resource for care management, finance, and analytics stakeholders — independently scoping questions, managing delivery, and communicating findings.&nbsp;</li></ul><p><em>Analytic modeling, infrastructure &amp; governance&nbsp;</em></p><ul><li>Write production-grade SQL for surveillance logic, benchmark modeling, and financial impact analysis against Snowflake for transformation and version control; participate actively in code review.&nbsp;</li><li>Maintain rigorous documentation of analytical definitions, business logic, data lineage, and surveillance rules so all work is reproducible, transferable, and audit-ready.&nbsp;</li><li>Identify gaps in data quality, analytical coverage, or pipeline reliability and proactively implement solutions; escalate patterns suggesting potential misconduct to Compliance and Legal with clear documentation.&nbsp;</li><li>Ensure all workflows maintain HIPAA compliance, PHI handling standards, CMS data use agreement terms, and Wellvana data governance policies.&nbsp;</li></ul>",
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      "description": "<p>Description</p><p> <strong>The Why Behind Wellvana:</strong></p><p>The healthcare system isn’t designed for health. We’re designed to change that. We’re Wellvana, and we help doctors deliver life-changing healthcare.  </p><p><br/>Through our elevated value-based care programs, we’re revitalizing an antiquated system that’s far too long relied on misaligned incentives that reward quantity of care not the quality of it. </p><p><br/>Our enlightened approach—covering everything from care coordination to clinical documentation education to marketing— ties the healthy outcomes of patients directly to shared savings for primary care providers, health systems and payors.  </p><p><br/>Providers in our curated network keep their independence, reduce their administrative headaches, and spend more time with patients. Patients, in turn, get an elevated experience with coordinated care between appointments that is nothing short of life-changing.  </p><p><br/>Named a 2024 \"Best in Business\" and 2023 \"Best Place to Work\" by Nashville Business Journal, we’re one of the fastest-growing healthcare companies in America because what we do works. This is the way medicine is meant to be.</p><p><br/><strong>Clarity on the Role:</strong></p><p>The Manager of Program Research is an analytically driven individual contributor who applies deep expertise in Medicare claims data and health economics modeling to one of the most consequential analytical challenges in ACO management: ensuring that Wellvana's measured performance reflects the reality of care delivered. </p><p><br/>Program Intelligence is Wellvana's function for identifying, analyzing, and responding to external claims behaviors, eligibility events, and utilization patterns that distort the ACO's benchmark, attributed population, or cost performance. This is a proactive analytical surveillance function at the intersection of claims data science, health economics, and value-based care program knowledge. </p><p><br/>You will own the full analytical lifecycle: designing surveillance logic, investigating flagged patterns, building financial impact models, and producing outputs that protect ACO shared savings. You operate with high autonomy as the primary analytical engine of the team. Program knowledge will be developed in role — what you bring is the analytical foundation that makes that learning fast and durable. </p><p><br/></p><p><br/><strong>What's Expected:</strong></p><p><br/></p><p><em>Claims-based surveillance & pattern detection </em></p><ul><li>Design, build, and maintain surveillance logic against Medicare claims data to detect external patterns affecting ACO benchmark, attribution, and cost calculations — including eligibility enrollment events, provider billing anomalies, and post-acute utilization patterns. </li><li>Develop and refine statistical thresholds and decision rules distinguishing meaningful signals from expected variation; identify emerging pattern types and build detection logic independently. </li><li>Manage surveillance data feeds — CMS claims refreshes, provider taxonomy data, eligibility events, post-acute episode chains — including quality monitoring and refresh cadence oversight. </li></ul><p><em>Investigation & financial impact modeling </em></p><ul><li>Review flagged patterns, apply documented decision rules to distinguish actionable signals from noise, and document findings — data sources, logic, disposition rationale — at the point of detection. </li><li>Build and maintain benchmark adjustment models quantifying financial impact on ACO shared savings position, including scenario ranges, documented assumptions, and sensitivity analysis. </li><li>Apply health economics methods — cost decomposition, risk adjustment analysis, utilization trending, population segmentation — to translate claims patterns into quantified financial findings with a complete longitudinal evidentiary record. </li></ul><p><em>Output development & stakeholder delivery </em></p><ul><li>Develop and deliver operational flags to care management and network teams formatted for direct workflow integration; produce quarterly financial impact summaries for finance and program leadership with narrative context non-technical stakeholders can act on. </li><li>Build audit-ready analytical packages supporting program-level decisions and, in collaboration with the department leader and legal, CMS submissions. </li><li>Serve as a direct analytical resource for care management, finance, and analytics stakeholders — independently scoping questions, managing delivery, and communicating findings. </li></ul><p><em>Analytic modeling, infrastructure & governance </em></p><ul><li>Write production-grade SQL for surveillance logic, benchmark modeling, and financial impact analysis against Snowflake for transformation and version control; participate actively in code review. </li><li>Maintain rigorous documentation of analytical definitions, business logic, data lineage, and surveillance rules so all work is reproducible, transferable, and audit-ready. </li><li>Identify gaps in data quality, analytical coverage, or pipeline reliability and proactively implement solutions; escalate patterns suggesting potential misconduct to Compliance and Legal with clear documentation. </li><li>Ensure all workflows maintain HIPAA compliance, PHI handling standards, CMS data use agreement terms, and Wellvana data governance policies. </li></ul><p>Requirements</p><p><strong>What's Required:</strong></p><p><br/></p><p><strong>Education </strong></p><ul><li>Bachelor's degree in health economics, statistics, mathematics, health informatics, public health, computer science, or a closely related quantitative field. </li></ul><p><strong>Years of Related Experience </strong></p><ul><li>5+ years of progressive experience in healthcare data analytics, health economics, or a closely related analytical field with demonstrated growth in scope and autonomy. </li><li>3+ years of direct, hands-on experience with Medicare claims data — CMS CCLF extracts, LDS files, or equivalent — including claim types (carrier, institutional, DME), revenue codes, HCPCS/CPT coding, and adjudication logic. </li><li>2+ years in a value-based care, ACO, or payer analytics environment — exposure to MSSP, ACO REACH, or comparable risk-bearing models preferred but not required. </li><li>2+ years applying health economics methods: cost decomposition, utilization trending, risk adjustment analysis, population segmentation, or financial impact modeling. </li><li>3+ years SQL, Python, R or dbt required. 2+ years Snowflake (preferred), BigQuery, or Redshift.. 2+ years BI platform (Sigma, Looker, Tableau, or Power BI). </li></ul><p><strong>Skills / Competencies / Behaviors </strong></p><ul><li>Deep fluency in Medicare claims data structures: MBI/HIC, NPI/TIN hierarchies, ICD-10-CM/PCS, CPT/HCPCS, revenue codes, place of service, claim adjustment reason codes, and provider specialty taxonomy. </li><li>Strong quantitative and statistical skills — design detection logic, identify outlier patterns in large datasets, build scenario models with documented assumptions, and communicate uncertainty and sensitivity clearly.  Familiarity with or genuine curiosity about large language models and AI-assisted coding tools — such as using LLMs for analytical code generation, documentation, or pattern interpretation — as part of a modern analytical workflowAbility to translate raw claims patterns into financial impact estimates actionable for non-technical audiences including finance leadership, care management, and program operations. </li><li>Working knowledge of Medicare risk adjustment (HCC v24/v28) and its role in ACO benchmark and performance measurement. </li><li>Self-directed and highly organized: manages multiple concurrent analytical workstreams, sets priorities independently, maintains documentation in real time, and delivers with minimal oversight. </li><li>Expert command of git and collaborative code review; all analytical work is production-grade, documented, and auditable. Proven track record of building durable analytical assets, not just one-off analyses. </li><li>Intellectual curiosity about how Medicare program mechanics, claims data patterns, and ACO financial performance interact — and genuine interest in developing deeper program expertise over time. </li></ul><p><strong>Preferred Qualities</strong></p><ul><li>Familiarity with CMS MSSP program mechanics — including benchmark methodology (rebasing, regional adjustment), attribution logic (plurality-based and voluntary alignment), shared savings and losses calculation, and the distinction between benchmark period and performance year dynamics. </li><li>Exposure to CMS annual final rules and sub-regulatory guidance updates — and experience translating regulatory changes into analytical requirements or updated data model logic. </li><li>Working knowledge of Medicare Advantage enrollment mechanics and their interaction with MSSP FFS attribution — including Annual Enrollment Period, Open Enrollment Period, and Special Enrollment Period dynamics and their compositional effects on the attributed population. </li><li>Familiarity with the governance boundary between program analytics functions and FWA/compliance functions — specifically, knowing when an identified utilization pattern warrants escalation to legal or compliance rather than operational response. </li><li>Experience with ACO REACH, CMMI innovation models, or other CMS alternative payment models in addition to MSSP. </li><li>Familiarity with population health platforms (Clarity by Wellvana, Arcadia, Lightbeam, or equivalent) and their data integration patterns. </li><li>Background in payer analytics, healthcare consulting practice, or health economics research environment. </li><li>Experience with HEDIS measure production, NCQA data submission, or equivalent quality program analytics. </li><li>dbt Certified Developer, Snowflake SnowPro Core, or equivalent cloud analytics platform credential. </li><li>Master's degree (MS in Health Economics, MPH, MS in Statistics, MHA, or equivalent) preferred. </li></ul>",
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    "requirements_html": "<p><strong>What's Required:</strong></p><p><br></p><p><strong>Education&nbsp;</strong></p><ul><li>Bachelor's degree in health economics, statistics, mathematics, health informatics, public health, computer science, or a closely related quantitative field.&nbsp;</li></ul><p><strong>Years of Related Experience&nbsp;</strong></p><ul><li>5+ years of progressive experience in healthcare data analytics, health economics, or a closely related analytical field with demonstrated growth in scope and autonomy.&nbsp;</li><li>3+ years of direct, hands-on experience with Medicare claims data — CMS CCLF extracts, LDS files, or equivalent — including claim types (carrier, institutional, DME), revenue codes, HCPCS/CPT coding, and adjudication logic.&nbsp;</li><li>2+ years in a value-based care, ACO, or payer analytics environment — exposure to MSSP, ACO REACH, or comparable risk-bearing models preferred but not required.&nbsp;</li><li>2+ years applying health economics methods: cost decomposition, utilization trending, risk adjustment analysis, population segmentation, or financial impact modeling.&nbsp;</li><li>3+ years SQL, Python, R or dbt required. 2+ years Snowflake (preferred), BigQuery, or Redshift.. 2+ years BI platform (Sigma, Looker, Tableau, or Power BI).&nbsp;</li></ul><p><strong>Skills / Competencies / Behaviors&nbsp;</strong></p><ul><li>Deep fluency in Medicare claims data structures: MBI/HIC, NPI/TIN hierarchies, ICD-10-CM/PCS, CPT/HCPCS, revenue codes, place of service, claim adjustment reason codes, and provider specialty taxonomy.&nbsp;</li><li>Strong quantitative and statistical skills — design detection logic, identify outlier patterns in large datasets, build scenario models with documented assumptions, and communicate uncertainty and sensitivity clearly. &nbsp;Familiarity with or genuine curiosity about large language models and AI-assisted coding tools — such as using LLMs for analytical code generation, documentation, or pattern interpretation — as part of a modern analytical workflowAbility to translate raw claims patterns into financial impact estimates actionable for non-technical audiences including finance leadership, care management, and program operations.&nbsp;</li><li>Working knowledge of Medicare risk adjustment (HCC v24/v28) and its role in ACO benchmark and performance measurement.&nbsp;</li><li>Self-directed and highly organized: manages multiple concurrent analytical workstreams, sets priorities independently, maintains documentation in real time, and delivers with minimal oversight.&nbsp;</li><li>Expert command of git and collaborative code review; all analytical work is production-grade, documented, and auditable. Proven track record of building durable analytical assets, not just one-off analyses.&nbsp;</li><li>Intellectual curiosity about how Medicare program mechanics, claims data patterns, and ACO financial performance interact — and genuine interest in developing deeper program expertise over time.&nbsp;</li></ul><p><strong>Preferred Qualities</strong></p><ul><li>Familiarity with CMS MSSP program mechanics — including benchmark methodology (rebasing, regional adjustment), attribution logic (plurality-based and voluntary alignment), shared savings and losses calculation, and the distinction between benchmark period and performance year dynamics.&nbsp;</li><li>Exposure to CMS annual final rules and sub-regulatory guidance updates — and experience translating regulatory changes into analytical requirements or updated data model logic.&nbsp;</li><li>Working knowledge of Medicare Advantage enrollment mechanics and their interaction with MSSP FFS attribution — including Annual Enrollment Period, Open Enrollment Period, and Special Enrollment Period dynamics and their compositional effects on the attributed population.&nbsp;</li><li>Familiarity with the governance boundary between program analytics functions and FWA/compliance functions — specifically, knowing when an identified utilization pattern warrants escalation to legal or compliance rather than operational response.&nbsp;</li><li>Experience with ACO REACH, CMMI innovation models, or other CMS alternative payment models in addition to MSSP.&nbsp;</li><li>Familiarity with population health platforms (Clarity by Wellvana, Arcadia, Lightbeam, or equivalent) and their data integration patterns.&nbsp;</li><li>Background in payer analytics, healthcare consulting practice, or health economics research environment.&nbsp;</li><li>Experience with HEDIS measure production, NCQA data submission, or equivalent quality program analytics.&nbsp;</li><li>dbt Certified Developer, Snowflake SnowPro Core, or equivalent cloud analytics platform credential.&nbsp;</li><li>Master's degree (MS in Health Economics, MPH, MS in Statistics, MHA, or equivalent) preferred.&nbsp;</li></ul>",
    "requirements_text": "What's Required:\n Education\n Bachelor's degree in health economics, statistics, mathematics, health informatics, public health, computer science, or a closely related quantitative field.\n Years of Related Experience\n 5+ years of progressive experience in healthcare data analytics, health economics, or a closely related analytical field with demonstrated growth in scope and autonomy.\n 3+ years of direct, hands-on experience with Medicare claims data — CMS CCLF extracts, LDS files, or equivalent — including claim types (carrier, institutional, DME), revenue codes, HCPCS/CPT coding, and adjudication logic.\n 2+ years in a value-based care, ACO, or payer analytics environment — exposure to MSSP, ACO REACH, or comparable risk-bearing models preferred but not required.\n 2+ years applying health economics methods: cost decomposition, utilization trending, risk adjustment analysis, population segmentation, or financial impact modeling.\n 3+ years SQL, Python, R or dbt required. 2+ years Snowflake (preferred), BigQuery, or Redshift.. 2+ years BI platform (Sigma, Looker, Tableau, or Power BI).\n Skills / Competencies / Behaviors\n Deep fluency in Medicare claims data structures: MBI/HIC, NPI/TIN hierarchies, ICD-10-CM/PCS, CPT/HCPCS, revenue codes, place of service, claim adjustment reason codes, and provider specialty taxonomy.\n Strong quantitative and statistical skills — design detection logic, identify outlier patterns in large datasets, build scenario models with documented assumptions, and communicate uncertainty and sensitivity clearly. Familiarity with or genuine curiosity about large language models and AI-assisted coding tools — such as using LLMs for analytical code generation, documentation, or pattern interpretation — as part of a modern analytical workflowAbility to translate raw claims patterns into financial impact estimates actionable for non-technical audiences including finance leadership, care management, and program operations.\n Working knowledge of Medicare risk adjustment (HCC v24/v28) and its role in ACO benchmark and performance measurement.\n Self-directed and highly organized: manages multiple concurrent analytical workstreams, sets priorities independently, maintains documentation in real time, and delivers with minimal oversight.\n Expert command of git and collaborative code review; all analytical work is production-grade, documented, and auditable. Proven track record of building durable analytical assets, not just one-off analyses.\n Intellectual curiosity about how Medicare program mechanics, claims data patterns, and ACO financial performance interact — and genuine interest in developing deeper program expertise over time.\n Preferred Qualities\n Familiarity with CMS MSSP program mechanics — including benchmark methodology (rebasing, regional adjustment), attribution logic (plurality-based and voluntary alignment), shared savings and losses calculation, and the distinction between benchmark period and performance year dynamics.\n Exposure to CMS annual final rules and sub-regulatory guidance updates — and experience translating regulatory changes into analytical requirements or updated data model logic.\n Working knowledge of Medicare Advantage enrollment mechanics and their interaction with MSSP FFS attribution — including Annual Enrollment Period, Open Enrollment Period, and Special Enrollment Period dynamics and their compositional effects on the attributed population.\n Familiarity with the governance boundary between program analytics functions and FWA/compliance functions — specifically, knowing when an identified utilization pattern warrants escalation to legal or compliance rather than operational response.\n Experience with ACO REACH, CMMI innovation models, or other CMS alternative payment models in addition to MSSP.\n Familiarity with population health platforms (Clarity by Wellvana, Arcadia, Lightbeam, or equivalent) and their data integration patterns.\n Background in payer analytics, healthcare consulting practice, or health economics research environment.\n Experience with HEDIS measure production, NCQA data submission, or equivalent quality program analytics.\n dbt Certified Developer, Snowflake SnowPro Core, or equivalent cloud analytics platform credential.\n Master's degree (MS in Health Economics, MPH, MS in Statistics, MHA, or equivalent) preferred."
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