Senior Data Scientist

About the Opportunity

A large hospital system in Texas is seeking a Senior Data Scientist to lead advanced analytics initiatives that drive data-informed decision-making across the organization. This role combines deep technical expertise in machine learning and statistics with strong business acumen, translating complex data into actionable insights for both technical and non-technical stakeholders. The ideal candidate thrives in a fast-paced, multidisciplinary environment and can independently manage multiple projects with competing priorities.

What You’ll Do

• Apply advanced machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) to real-world business and clinical problems, weighing their practical advantages and limitations
• Design and execute analyses using advanced statistical techniques (regression, distribution properties, statistical testing, A/B testing, time series forecasting, etc.)
• Manage the full data science project life cycle, from requirements gathering through modeling, validation, and delivery
• Research and resolve data issues within large, complex, and often incomplete datasets
• Communicate findings and recommendations through clear data storytelling for both technical and business audiences
• Partner across IT and business teams to gather requirements, scope projects, and align analytics work with organizational priorities
• Independently manage multiple concurrent projects, balancing competing priorities while meeting goals and deadlines
• Troubleshoot data and analytical issues, recommending sound, practical solutions
• Provide high-quality work products and project management reflecting strong customer service standards, including in challenging stakeholder situations

What We’re Looking For

• Seven (7) years of experience in data science
• Strong business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills, and understanding of design and architecture principles
• Deep understanding of a variety of machine learning techniques and their real-world advantages/drawbacks
• Proficient understanding of advanced statistical techniques and concepts, with hands-on application experience
• Advanced-level knowledge of the data science project life cycle
• Proficient programming skills and working knowledge of statistical analysis tools
• Advanced understanding of SQL database management tools
• Advanced knowledge of data science methods, including time series forecasting, linear regression, A/B testing, statistical testing, and clustering
• Strong written and verbal communication skills, with the ability to translate complex information for a wide range of stakeholders
• Demonstrated proficiency in problem-solving, analytical reasoning, and decision-making
• Ability to work under minimal supervision in a fast-paced, multidisciplinary environment
• Strong project management skills, including the ability to work independently across multiple projects with competing priorities