Data Scientist

Empower Pharmacy is a visionary healthcare company dedicated to making quality, affordable medication accessible to millions of patients nationwide. As the nation’s most advanced 503A compounding pharmacy and FDA-registered 503B outsourcing facility, we’re redefining what’s possible in personalized medicine and pharmaceutical manufacturing. We’re proud to be recognized as one of Houston’s fastest-growing private companies and ranked #116 in Healthcare & Medical on the Inc.

5000 List for 2025.

Our strength is built on four core values:
People, Quality, Service, and Innovation. Guided by these principles, we’ve created a uniquely integrated healthcare platform powered by advanced technology, operational excellence, and a relentless commitment to patient care. From manufacturing and quality control to distribution and customer experience, our teams work together to raise industry standards, expand access to critical medications, and improve outcomes for patients and providers across the country.

At Empower, joining our team means more than starting a new role. It means becoming part of a mission-driven organization that’s transforming healthcare  invest deeply in our people, encourage bold thinking, and create opportunities for growth, leadership, and innovation at every level. Your ideas matter here, your development is supported, and the work you do has a direct impact on the lives of millions.

If you thrive in a fast-moving, purpose-driven environment where innovation, collaboration, and ambition come together, Empower Pharmacy is the place for you. Let’s transform healthcare together.

The Data Scientist drives business impact by translating complex enterprise data into trusted, decision-ready intelligence that improves quality, accelerates growth, and optimizes operations across Empower’s hyper-growth 503A/503B environment. This role executes end-to-end data science initiatives, from problem framing and data preparation through model development, validation, interpretation, and communication, delivering scalable analytical solutions that support measurable business outcomes. Leveraging AI as a force multiplier, the role increases the speed, scale, and precision of analysis while applying strong statistical judgment, rigorous experimentation, and disciplined validation.

Partnering cross-functionally, the Data Scientist identifies patterns, quantifies opportunities, evaluates tradeoffs, and translates findings into actionable insights that enable sound execution. The role demonstrates strategic thinking, rigorous execution, and learning agility to navigate evolving priorities, challenge assumptions, and continuously strengthen analytical capabilities while maintaining privacy, traceability, compliance, patient safety, and human accountability.

Analytical Ownership

• Problem Framing: Translate ambiguous business questions into precise analytical problems, define success measures, and select methods that produce actionable, decision-ready outputs.
• Data Preparation: Build reliable analytical datasets by assessing data quality, resolving inconsistencies, documenting assumptions, and preserving traceability from source through final analysis.
• Model Development: Develop and evaluate statistical or predictive models using appropriate techniques, balancing performance, interpretability, robustness, and practical business requirements.

Business Partnership

• Insight Delivery: Communicate findings, uncertainty, tradeoffs, and recommended actions clearly to cross-functional partners, enabling timely decisions grounded in evidence and business context.
• Experiment Design: Design rigorous analyses and experiments that test hypotheses, quantify impact, and distinguish meaningful signals from noise before operational decisions are made.
• Decision Support: Apply AI-assisted analytical techniques where appropriate to accelerate pattern identification and scenario evaluation while validating outputs and preserving accountable human judgment.

Regulated Excellence

• Quality Controls: Validate analytical methods, outputs, and assumptions through repeatable checks, documentation, and peer review…