Senior Director, Strategic Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Director, Strategic Analytics based in United States.

This is a senior individual contributor role operating at the intersection of clinical medicine, healthcare quality, applied data science, and AI. You will use deep clinical and informatics expertise to develop algorithms that identify documentation, coding, and clinical care gaps. Your work will directly influence risk adjustment, quality attribution, mortality outcomes, and performance against major hospital ranking and rating methodologies. The role combines hands-on Databricks engineering with advanced AI/ML development across EHR, claims, coding, and quality data. You will work closely with clinical, quality, CDI, coding, analytics, IT, and executive stakeholders to turn complex insights into measurable performance improvements. With director-level strategic scope and significant executive visibility, you will help shape multi-year strategies while remaining deeply involved in technical delivery. This is an opportunity to build innovative healthcare intelligence solutions that can improve both clinical outcomes and organizational performance.

Accountabilities: Maintain expert-level knowledge of major hospital ranking, rating, and benchmarking methodologies, including CMS Star Ratings, Value-Based Purchasing, Hospital-Acquired Condition programs, U.S. News & World Report, Leapfrog, Vizient, Healthgrades, and payer-specific quality programs.

Translate risk-adjustment models, attribution logic, inclusion and exclusion criteria, observed-to-expected ratios, and other methodology specifications into actionable data requirements and analytical models.

Serve as a senior clinical and quality subject-matter expert connecting clinical operations, coding/CDI, quality, analytics, IT, and executive leadership.

Advise senior clinical and executive leaders on methodology changes, ranking trends, quality strategy, investment priorities, and reputational risks.

Design, build, validate, and productionize AI/ML and rules-based algorithms that identify documentation and coding gaps affecting severity of illness, mortality risk, HCC/risk adjustment, and quality attribution.

Develop models that detect variation in clinical processes, including core measure compliance, sepsis bundle adherence, readmission drivers, mortality outliers, and other factors affecting benchmarked outcomes.

Apply NLP and LLM techniques to clinical notes, structured EHR information, coded claims, and other healthcare datasets to identify clinically meaningful and actionable insights.

Build, optimize, and maintain scalable Databricks data pipelines and feature stores using technologies such as Delta Lake, PySpark, MLflow, and Unity Catalog.

Develop and deploy predictive and generative AI solutions within a Databricks Lakehouse environment, incorporating model monitoring, versioning, governance, security, privacy, and auditability.

Partner with CDI, coding, quality, and clinical leaders to translate algorithmic findings into practical workflow changes and performance-improvement initiatives.

Establish a multi-year strategic roadmap for hospital ranking and rating performance in collaboration with executive sponsors and business leadership.

Develop benchmarking dashboards and predictive indicators that provide clinical and executive teams with early visibility into performance trajectories.

Recommend and prioritize clinical process improvements by connecting algorithm findings to specific ranking and quality levers.

Present complex analytical findings and strategic recommendations to physicians, quality committees, clinical leadership, and C-suite stakeholders in clear, credible, data-driven terms.

Influence priorities across multiple functions without direct management authority and provide mentorship and technical guidance to analysts and data scientists.

Drive initiatives end-to-end, from developing clinical hypotheses and analytical approaches through deploying algorithms and translating results into executive-level recommendations.

Requirements

Clinical licensure or credentialing such as RN, MD/DO, PharmD, or an equivalent clinical degree, or a graduate degree in Clinical/Health Informatics combined with substantial hands-on clinical quality experience.

10+ years of experience in clinical informatics, clinical quality, CDI, population health analytics, or a related discipline, including direct experience with hospital ranking and rating methodologies.

At least 5 years of hands-on experience developing data pipelines and/or machine learning models in Databricks, with strong proficiency in Spark, Delta Lake, MLflow, SQL, and Python.

Demonstrated experience applying AI/ML, including NLP and LLM techniques, to clinical or claims data for gap detection, risk stratification, quality measurement, or related healthcare applications.

Deep knowledge of ICD-10-CM/PCS coding and risk-adjustment methodologies such as APR-DRG, MS-DRG, and HCC/RAF, including how documentation and coding quality influence publicly reported outcomes.

Strong understanding of healthcare data environments, clinical quality measurement, and the relationship between clinical processes, documentation, coding, and organizational performance.

Ability to operate independently as a senior individual contributor with director-level scope, high autonomy, and executive visibility.

Demonstrated ability to take complex initiatives from clinical hypothesis through technical development, production deployment, performance improvement, and executive recommendation.

Excellent communication and presentation skills, with the ability to translate technical, statistical, and clinical findings for physicians, executives, and non-technical stakeholders.

Strong strategic thinking, analytical reasoning, problem-solving, stakeholder management, and cross-functional collaboration skills.

Experience working across matrixed healthcare environments involving quality, coding/HIM, clinical operations, IT, analytics, and executive leadership is highly valuable.

A Master's or doctoral degree in Clinical Informatics, Health Data Science, Public Health, Nursing, Medicine, or a related field is preferred.

Direct experience improving performance against U.S. News, CMS Star Ratings, Leapfrog, Vizient, or comparable hospital benchmarking programs is preferred.

Experience with Databricks Unity Catalog, Genie/AI-BI tools, MLOps, or AI development within regulated healthcare environments is advantageous.

Familiarity with FHIR, HL7, and EHR data models such as Epic Clarity/Caboodle or Cerner is a plus.

Prior experience serving as a strategic advisor to C-suite or senior executive leadership is preferred.

Benefits

Base salary range of $157,250–$212,750 , with final compensation based on factors including geography and experience.

Equity package.

Annual bonus opportunities.

Medical, dental, and vision insurance.

Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA).

Company-paid life insurance.

Company-paid short-term and long-term disability coverage.

401(k) retirement plan.

Company-paid holidays.

Flexible time off.

Employee wellness program.

Additional voluntary benefits.

Opportunity to work on innovative healthcare AI, analytics, and quality-improvement initiatives with significant executive visibility.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1