Senior Principal Data Scientist - Retail Analytics

CVS Health•New York, NY

About The Position

Defines and drives enterprise‑scale analytical vision, leading the invention, validation, and institutionalization of novel, highly complex algorithms, statistical models, and advanced machine learning approaches that address the organization’s most ambiguous and high‑impact business problems. Sets the highest standard for analytical rigor across the enterprise, establishing advanced statistical frameworks, modeling paradigms, and methodological best practices that govern how complex, multi‑source data is interpreted, stressed, and translated into decision‑grade insights. Owns the conception and orchestration of the most complex analytical initiatives, spanning exploratory research, feature engineering, model architecture design, large‑scale experimentation, validation, performance monitoring, and long‑term sustainability of solutions. Serves as the organization’s top‑tier authority across systems, products, and data ecosystems, proactively advising senior leaders and cross‑functional partners on where advanced analytics should be applied to unlock enterprise value, mitigate systemic risk, or enable new strategic capabilities. Shapes and advances enterprise analytic talent and capability, mentoring other senior and principal‑level scientists, pressure‑testing technical approaches, and cultivating deep technical judgment across the analytics community. Provides recognized thought leadership by defining long‑term analytic solution strategies, influencing platform evolution, and advancing the organization’s use of emerging techniques, toolsets, and theoretical advances well ahead of industry norms. Anticipates and resolves the most complex, high‑risk, and strategically sensitive business challenges, applying leading‑edge theories and advanced quantitative techniques to identify non‑obvious patterns, test assumptions, and recommend solutions with enterprise‑wide impact. Architects and governs the enterprise analytics strategy and roadmap, ensuring alignment between business strategy, product direction, data assets, and advanced analytical capabilities across multiple domains. Influences at the executive and external‑peer level, communicating highly complex analytical concepts, trade‑offs, and recommendations with clarity and authority to gain alignment, shape strategic decisions, and secure adoption of new or disruptive analytic approaches.

Requirements

12+ years of progressively advanced experience in data science, advanced analytics, or applied research roles demonstrating sustained impact at enterprise scale
Demonstrated mastery of advanced analytics languages, platforms, and architectures, with a proven ability to design and operationalize solutions across highly complex, heterogeneous data environments.
Recognized expertise in inventing, adapting, and deploying novel machine learning and statistical techniques, particularly in settings characterized by scale, ambiguity, and strategic risk.

Nice To Haves

Excellent analytical and problem-solving skills
Strong organizational, management and leadership skills
Comprehensive knowledge of the health care industry, products, systems, business strategies and products
Demonstrates advanced in-depth specialization in mathematical analysis methods, machine learning, statistical analyses, and predictive modeling
Superior ability to communicate technical ideas and results to non-technical clients in written and verbal form
Superior skills to effectively communicate and negotiate across business and in the external health care environment

Responsibilities

Defines and drives enterprise‑scale analytical vision, leading the invention, validation, and institutionalization of novel, highly complex algorithms, statistical models, and advanced machine learning approaches.
Sets the highest standard for analytical rigor across the enterprise, establishing advanced statistical frameworks, modeling paradigms, and methodological best practices.
Owns the conception and orchestration of the most complex analytical initiatives, spanning exploratory research, feature engineering, model architecture design, large‑scale experimentation, validation, performance monitoring, and long‑term sustainability of solutions.
Serves as the organization’s top‑tier authority across systems, products, and data ecosystems, proactively advising senior leaders and cross‑functional partners on where advanced analytics should be applied.
Shapes and advances enterprise analytic talent and capability, mentoring other senior and principal‑level scientists, pressure‑testing technical approaches, and cultivating deep technical judgment.
Provides recognized thought leadership by defining long‑term analytic solution strategies, influencing platform evolution, and advancing the organization’s use of emerging techniques.
Anticipates and resolves the most complex, high‑risk, and strategically sensitive business challenges, applying leading‑edge theories and advanced quantitative techniques.
Architects and governs the enterprise analytics strategy and roadmap, ensuring alignment between business strategy, product direction, data assets, and advanced analytical capabilities.
Influences at the executive and external‑peer level, communicating highly complex analytical concepts, trade‑offs, and recommendations with clarity and authority.