Principal Decision Scientist, Strategy & Innovation

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. The Signify Health Strategy & Innovation team is responsible for shaping the company’s long-term strategy, discovering opportunities to accelerate growth, and identifying and testing net new offerings or capabilities. The team serves in an advisory capacity to Signify’s Executive Leadership Team (ELT) - partnering closely with leaders to evaluate challenges and opportunities, facilitate decision-making, and execute early-stage proofs of concept. The Principal Decision Scientist , reporting to the Vice President of Innovation, is the team's first dedicated quantitative hire to bring additional rigor to strategy as an individual contributor who designs and builds the causal inference studies and sizing analyses that underpin Signify's highest-visibility strategic recommendations. Work falls into two buckets: (i) (i) leading deep statistical studies to prove member outcomes and (ii) providing quantitative sizing to guide decisions on new growth opportunities. The individual will also (iii) be responsible to collaborate across Signify’s business functions, including with other data professionals to standardize and improve technical fundamentals, documentation, code reviews, data models, and quality controls. Ideal candidates are data-driven, inquisitive, autonomous, and entrepreneurial thinkers who can collaborate effectively across functions and with executive leadership. Position Responsibilities (i) Clinical Evidence Generation & Member Insights Extract knowledge and insights from data in order to investigate complex business problems through a range of data preparation, modeling, analysis and/or visualization techniques, including predictive analysis, business intelligence, pattern recognition, operational effectiveness and/or economic forecasting Design, build, and maintain causal inference studies that quantify the member-level clinical outcomes of the in-home health evaluation, supporting workflow and service enhancements Build and validate proof of concepts to identify rich, incremental member insights , leveraging health plan data combined with Signify's in-home insights. Potential approaches include statistical analysis, machine learning, and other applied methods (ii) Analytic Support of Strategic and Growth Evaluations Translate ambiguous, open-ended business questions into structured analytical approaches, partnering with strategy and business function leaders Conduct new product and partnership opportunity sizings by analyzing Signify's internal operational and clinical data , supplemented by publicly available data where needed (iii) Analytic Best Practices and Cross-Company Collaboration Champion analytics best practices , e.g. engineering standards, version control, code review, documented pipelines, common data sources, with other analytic leaders within Signify to improve quality, repeatability, and ability to build off each other's work Act as a technical thought partner and mentor to analytics talent across the organization Bring a creative, structured approach to pressure-testing methodology and hypotheses across the full active portfolio, not only assigned workstreams Present analysis directly to Signify's ELT and executive leadership , as workstream lead or in support of a strategy lead, building credibility and influence at the executive level Required Qualifications Decision / Data Science Technical Requirements SQL : expert-level, hands-on querying and manipulation of large healthcare datasets; ability to size new offerings leveraging internal databases Python : hands-on use for statistical analysis, modeling, automation, and exploratory / explanatory data visualization Statistics : strong grounding in applied statistics, hypothesis testing, regression, distributional reasoning, sufficient to defend methodology choices Causal inference : demonstrated experience applying causal inference methods to real business decisions In addition to other relevant data analysis techniques (e.g., A/B testing, association rule learning, cluster analysis, pattern recognition and predictive modeling), data analysis and visualization software, object-oriented programming languages (Python, Java, R, Ruby, Scala, C++) and/or data engineering skills (relational or NoSQL databases, ETL tools) Experience working with Snowflake (primary platform) and/or other cloud platforms (e.g. GCP, AWS, Asure) Additional Required Experience 10+ years of experience in applied quantitative analysis, decision science, or data science , with direct, hands-on ownership of analyses (including academia but with a preference for industry experience) Healthcare industry experience with hands-on data experience : notably with health plan payer data (e.g. claims, lab data, enrollment, SDOH, etc.). Experience with unstructured provider clinical data is preferred Track record of introducing or materially improving analytics best practices Executive presence : demonstrated ability to present complex, technical analysis directly to senior executive audiences and build credibility and influence at that level Strong written communication skills , with experience producing analysis that non-technical stakeholders can act on without the author present to narrate it. Preferred Qualifications Familiarity with CMS risk adjustment and STARS quality methodologies Experience building and validating machine learning models or proof-of-concepts (e.g., predictive risk models, member insight models) as a complement to causal inference methods Demonstrated comfort operating with significant ambiguity : translating an open-ended business question into a structured analytical plan Experience operating in a flat or matrixed organization Location: Chicago or New York City is preferred (WFH or Hybrid), but not required; ability to travel 10-20% of the time Education Bachelor's degree in a quantitative field required (statistics, economics, applied mathematics, data science, computer science, or related) Master's degree in a quantitative field strongly preferred Pay Range The typical pay range for this role is: $144,200.00 - $288,400.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program. Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong. Great benefits for great people We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. Additional details about available benefits are provided during the application process and on Benefits Moments . We anticipate the application window for this opening will close on: 11/29/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.