Supervisor, Data Science, Analytics & AI

Supervises and leads SCEA Analytics and Data Science teams. Provides leadership in leveraging analytics in proven and innovative ways to transform care, streamline operations and unify decision making. Integrates and sustains standardized data science, AI and analytic tools & methodologies, driving data fluency across the organization. As an leader, contributes to creating a data-driven culture. Establishes a systematic approach and standards for leveraging analytics in business and clinical operations. Leads the organization in utilizing data for strategic thinking, quality improvement, planning and operational and financial management. Leads the development and adoption of organizational key performance indicators (KPI's) and predictive analytics. Partners with senior leadership, SCEA Delivery Teams and organization teams to implement and support long-term analytic solutions.

  

Required Education and Experience
Bachelor’s degree in Operations Research, Statistics, Business Administration, Healthcare Administration, Healthcare Informatics, Public Health, Data Science or related field. At least two (2) years experience in program, project or personnel leadership roles. At least seven (7) years progressively responsible experience in data analysis or data science role in a healthcare setting. Minimum of five (5) years experience with clinical, hospital, and/or financial applications. Experience working as a cross-functional team member and a team leader in a complex setting. Highly skilled in statistics as well as machine learning/data mining/generative AI etc., including experience with different paradigms of statistical inference (frequentist, Bayesian, information-theoretic) and differences between modeling for explanation and modeling for prediction. Significant experience developing and using statistical models and algorithms to drive business or clinical value. - Advanced experience with at least one notable BI reporting tool (e.g. Tableau, PowerBI, Looker) - Expert knowledge of data analysis and display techniques Advanced experience in least one data science language (e.g., R, Python). Expert in use of data visualization for non-technical audiences. Experience working with source control tools and version management. Experience in data extraction. Leadership and management experience, including managing personnel, projects, or programs, and budgeting for direct reports and/or projects. Experience working directly with technical and non-technical senior leadership on topics relating to integrated data analytics and data science products and solutions supporting enterprise-level goals and priorities.

Required Credentials


Preferred
Master’s degree in data science, analytics, statistics, public health or engineering.

Compensation Range

$139,486.00 - $209,228.00 per year

Salary Information

This compensation range was calculated based on full-time employment (2080 hours worked per calendar year). Offers are determined by multiple factors including equity, skills, experience, and expertise, and …