Staff Data Scientist

Position Summary

The 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.

Responsibilities

Enterprise Data Science

• Strategic Ownership: Lead high-impact, cross-functional data science initiatives from problem framing through deployment, ensuring alignment with enterprise priorities and delivering measurable business outcomes.
• Solution Design: Design advanced analytical models, experimentation frameworks, and optimization strategies that translate ambiguous business challenges into structured, high-value solutions.
• Impact Delivery: Embed data science into operational workflows, ensuring solutions are actionable, interpretable, sustainable, and continuously improved through feedback loops, monitoring, and AI-enabled automation.

Advanced Analytics Execution

• Model Development: Develop and deploy sophisticated models, including forecasting, causal inference, and optimization, ensuring technical rigor and business relevance.
• Experimentation Design: Establish robust experimentation and measurement frameworks, defining KPIs and success criteria that enable confident, data-driven decisions.
• Data Utilization: Transform complex datasets into high-quality analytical assets, ensuring data integrity and accessibility for modeling and reporting.