Staff Data Scientist

Position Summary

Staff Data Scientist drives enterprise impact by translating complex data into scalable, decision-ready intelligence that accelerates growth, improves quality, and optimizes regulated operations. This role owns end-to-end data science initiatives across functions, shaping strategy, execution, and measurable outcomes while influencing senior leadership decisions. Leveraging AI as a force multiplier, the role increases speed, scale, and precision of insights, enabling superior forecasting, experimentation, and optimization. Operating within Empower’s hyper-growth 503A/503B environment, this position ensures compliant, high-quality, and auditable analytics at scale. The role demonstrates exceptional strategic thinking, rigorous execution, and rapid learning agility to navigate ambiguity, challenge assumptions, and continuously elevate enterprise data science capabilities and business performance while building frameworks, mentoring peers, and institutionalizing best practices that sustain long-term value creation and regulatory confidence across the organization.

Duties and Responsibilities

Enterprise Data Science

• Strategic Ownership: Leads high-impact, cross-functional data science initiatives from problem framing through deployment, ensuring alignment with enterprise priorities while delivering measurable business outcomes through scalable, production-ready solutions that integrate AI to enhance decision speed, operational efficiency, and predictive accuracy across regulated environments.
• Solution Design: Designs advanced analytical models, experimentation frameworks, and optimization strategies that translate ambiguous business challenges into structured, high-value solutions, leveraging AI and modern data platforms to improve quality, scalability, and real-time decision-making across diverse functional domains.
• Impact Delivery: Drives measurable business impact by embedding data science into operational workflows, ensuring solutions are actionable, interpretable, and sustainable, while continuously improving performance through feedback loops, monitoring, and AI-enabled automation that enhances consistency, compliance, and enterprise-wide adoption.

Advanced Analytics Execution

• Model Development: Develops and deploys sophisticated models including forecasting, causal inference, and optimization, ensuring technical rigor and business relevance while leveraging AI techniques to accelerate model iteration, improve predictive performance, and scale insights across high-volume, regulated processes.
• Experimentation Design: Establishes robust experimentation and measurement frameworks, defining KPIs and success criteria that enable confident, data-driven decisions while using AI to enhance test design, automate analysis, and improve the speed and reliability of insights generation.
• Data Utilization: Transforms complex datasets into high-quality analytical assets, ensuring data integrity, governance, and usability while applying AI-driven feature engineering and data processing techniques to unlock deeper insights and support scalable, enterprise-grade analytics solutions.

Stakeholder Influence And Innovation

• Executive Partnership: Partners with senior leaders to identify opportunities, challenge assumptions, and shape data-driven strategies, translating complex findings into clear, actionable insights that influence high-stakes decisions and align with business objectives and regulatory expectations.
• Insight Communication: Communicates complex analytical results through compelling narratives and visualizations, ensuring clarity, trust, and adoption while leveraging AI tools to enhance storytelling, automate reporting, and deliver insights at the speed required for a hyper-growth environment.
• Capability Building: Elevates organizational data science maturity by mentoring peers, promoting best practices, and introducing innovative methodologies and AI capabilities that enhance efficiency, scalability, and long-term value creation across the enterprise.

Knowledge and Skills

• Advanced expertise in Python, SQL, and modern data platforms with strong capabilities in forecasting, experimentation, optimization, and causal inference applied to large-scale business problems.
• Deep understanding of AI/ML techniques and their application to improve speed, scale, decision quality, and automation within complex, regulated environments.
• Strong business acumen with the ability to translate ambiguity into structured analytical approaches and communicate insights effectively to executive stakeholders.
• Proficiency in designing KPIs, measurement frameworks, and scalable analytics solutions that ensure data integrity, governance, and operational impact.

Key Competencies

• Customer Focus: Builds trust through customer-centric solutions
• Strategic AI: Guides responsible AI adoption and adaptation
• Optimizes Work Processes: Drives efficiency with continuous improvement
• Collaborates: Partners effectively to achieve shared goals
• Resourcefulness: Secures and deploys resources efficiently
• Manages Complexity: Simplifies and solves complex challenges
• Ensures Accountability: Delivers on commitments with integrity
• Situational Adaptability: Adjusts approach to shifting conditions
• Communicates Effectively: Tailors messages to diverse audiences

Values

• People: Empowering people defines who we are
• Quality: Excellence in every product, every time
• Service: Serving others is our highest purpose
• Innovation: Advancing care through technology and discovery

Experience And Qualifications

• A minimum of 8 years of experience in data science, advanced analytics, statistics, operations research, or a related quantitative field, including ownership of large-scale or cross-functional initiatives.
• Requires a bachelor’s degree in statistics, data science, applied mathematics, economics, computer science, engineering, or a related discipline; a master’s degree is preferred and a PhD is a plus.
• Strong strategic thinking, executive communication, cross-functional collaboration, stakeholder influence, and the ability to solve complex problems in ambiguous environments while driving alignment without direct authority.
• Deep technical expertise in Python, Structured Query Language (SQL), experimentation, causal inference, forecasting, optimization, KPI and measurement framework design, decision-support analytics, and experience with modern data platforms such as Snowflake, Amazon Web Services (AWS), and Microsoft Azure.
• Preferred: certification in statistics, experimentation, forecasting, optimization, or causal inference.

Benefits

Employee Benefits, Health and Wellness:

We offer comprehensive benefits to support your health, well-being, and future, including medical, dental, and vision coverage, paid time off, 401(k) matching, wellness perks, IV therapy, and compounded medications.

Learn more: https://careers.empowerpharmacy.com/benefits/

Physical Requirements

While performing the responsibilities of the job, the employee is required to talk and hear. The employee is often required to remain in a stationary position for a significant amount of the workday and frequently use their hands and fingers to handle or feel in order to access, input, and retrieve information from the computer and other office productivity devices. Employees are regularly required to move about the office and around the corporate campus. The employee is regularly required to stand, walk, reach with arms and hands, climb or balance, and to stoop, kneel, crouch or crawl.