Remote Sr. Director, Healthcare Analytics

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them.

About the Role

The Remote Senior Director, Healthcare Analytics is accountable for building and leading the organization’s program evaluation and causal analytics capability. This role designs and executes rigorous assessments of clinical, operational, and benefit interventions (e.g., care management, utilization management, pharmacy programs, network initiatives, supplemental benefits, and value-based arrangements). The leader translates healthcare data into credible causal impact estimates, quantifies savings/ROI and quality outcomes, and establishes evaluation standards, governance, and analytic best practices across the enterprise. This role partners closely with Clinical Operations, UM, Finance, Product, Network, and IT/Data teams to ensure interventions are designed with measurable outcomes and are evaluated using defensible methods appropriate for Medicare Advantage and value-based care contexts.

Responsibilities

• Program Evaluation Leadership (Core):
  • Own the end-to-end evaluation strategy for priority interventions, including study design selection, cohort definitions, outcome specifications, measurement windows, and analytic plans (pre/post, matched cohorts, quasi-experimental approaches).
  • Design and execute causal inference evaluations using:
    • Propensity score methods (matching/weighting/stratification; overlap checks; sensitivity analyses).
    • Difference-in-differences (parallel trends diagnostics; event-study variants; staggered adoption when applicable).
    • Related approaches as appropriate (e.g., inverse probability weighting, regression adjustment).
  • Establish and maintain an evaluation “playbook”: standardized templates for research questions, inclusion/exclusion criteria, baseline checks, attribution rules, risk adjustment, and reporting conventions to ensure repeatable, auditable analyses.
  • Quantify intervention impact across cost, utilization, and quality: PMPM savings, avoidable utilization, inpatient/ED, readmissions, medication adherence, care gaps, Stars-related measures, and operational KPIs.
• Measurement, Governance, and Stakeholder Partnership:
  • Partner with operational and clinical leaders to establish standards for each program for measurement (clear triggers, timing, enrollment criteria, exposure definitions) and to ensure feasibility of evaluation before implementation.
  • Support cross-functional governance of metric definitions and analytic standards across IT, Finance, Clinical, and Operations to ensure consistent, trusted results.
  • Translate complex causal and statistical findings into clear executive narratives: what changed, why it likely changed, confidence/uncertainty, risks/limitations, and recommended actions.
• Data, Methods, and Analytic Excellence:
  • Work hands-on with medical/pharmacy claims, enrollment, provider, and operational data to validate assumptions, troubleshoot anomalies, and ensure analytic integrity.
  • Promote best practices in data quality, reproducibility, and version control (transparent code, documentation, cohort logic traceability).
  • Develop and maintain analytic assets (reusable code modules, cohort builders, standardized outcome tables, dashboards) that enable scalable evaluation across many programs.
  • Provide methodological guidance for:
    • Power / minimum detectable effect reasoning and prioritization (where data volume permits).
    • Handling confounding, selection bias, regression-to-mean, and contamination.
    • Appropriate risk adjustment and segmentation (clinical risk, RAF/HCC, social risk proxies where permitted).
• Advanced Economic / Statistical Analyses (Desired but Not Required):
  • Apply or oversee advanced methods such as:
    • Demand modeling (e.g., discrete choice / BLP-style frameworks) for benefit design, network steerage, or product features.
    • Panel / longitudinal methods (fixed effects, random effects, generalized estimating equations) for repeated-measures outcomes.
    • Time-to-event / survival analysis for churn, persistence, timing of utilization, or program exposure duration.
    • Causal event-time models for phased rollouts and operational changes.
• Supervisory Responsibilities:
  • Oversee assigned staff, including recruiting, selecting, orienting, and training employees; assigning workload; planning, monitoring, and appraising job results; and coaching, counseling, and disciplining employees.

Requirements

• Minimum Experience:
  • 10+ years of experience in healthcare analytics, actuarial science, medical economics, statistics/econometrics, or a closely related quantitative field, with significant experience evaluating healthcare interventions.
  • 6+ years of people leadership and/or matrix leadership experience, including leading senior individual contributors and influencing cross-functional executives.
  • Demonstrated track record delivering credible program evaluation results used to make operational and financial decisions (e.g., scale/stop/redesign programs).
• Education/Licensure:
  • Bachelor’s degree in a quantitative field (Actuarial Science, Statistics, Econometrics, Mathematics, Data Science, Economics, Engineering, or similar).
  • Advanced degree preferred (MS/PhD in Statistics, Biostatistics, Economics, Public Health, or related).
  • Actuarial credential preferred (ASA/FSA) or equivalent evidence of advanced quantitative mastery.
• Required Technical / Methodological Skills:
  • Propensity score methods: matching/weighting, overlap/common support, sensitivity checks.
  • Difference-in-differences: model specification, parallel trends testing, event-study interpretation, and communicating limitations.
  • Strong command of statistical modeling and inference; ability to select appropriate methods and explain why they are appropriate.
  • Advanced proficiency with healthcare data (medical/pharmacy claims, enrollment, provider, utilization/authorization feeds), including cohort construction and outcome measurement.
  • SQL required; R or Python strongly preferred, including ability to write production-quality analytic code and build reusable evaluation pipelines.
• Domain Knowledge / Business Skills:
  • Deep understanding of healthcare financing and value-based care measurement; ability to connect evaluation outcomes to ROI, affordability, quality, and operational performance.
  • Strong executive communication skills—able to distill complex causal results into clear recommendations and decision-ready deliverables.
  • Demonstrated ability to establish governance and standardization across teams (definitions, data lineage, reproducibility, and analytic QA).
• Desired (Not Required):
  • Experience with demand modeling (e.g., BLP/discrete choice), panel/longitudinal methods, and/or survival/time-to-event analysis for churn/timing.
  • Experience evaluating programs in Medicare Advantage and/or strong familiarity with MA performance drivers (e.g., Stars-related quality measures, risk adjustment/RAF, benefit design economics).

Pay

Pay Range: $172,364.00 - $258,547.00. Pay range may be based on a number of factors including market location, education, responsibilities, and experience.