Data Analyst/Scientist IV

Job Summary:

Leads advanced analytics initiatives that transform complex data into strategic insights and measurable business impact. Oversees the design and execution of predictive modeling, machine learning, and statistical studies that forecast outcomes, inform decisions, and drive operational excellence. Applies deep technical expertise in tools such as SAS, SQL, R, Python, and Tableau to identify trends, variances, and opportunities for improvement, ensuring analyses are clear, actionable, and aligned with organizational priorities. Partners with senior leadership and research teams to uphold scientific rigor in study design, data validity, and methodological integrity, establishing scalable analytic practices that strengthen quality, efficiency, and innovation across the enterprise.

Essential Functions:

• Leads the design and implementation of advanced data analysis strategies, including statistically sound sampling methodologies, predictive modeling, and trend analysis to identify opportunities, variances, and outliers that drive quality improvement and focused investigations.
• Develops and applies epidemiologically sound indicators and benchmarks to assess performance and quality of care, ensuring analyses align with established standards and comparative frameworks.
• Mentors junior data analysts and scientists in advanced methodologies, coding practices, and statistical interpretation, fostering technical growth and methodological rigor across the team.
• Designs and implements high-performance algorithms and machine learning models within distributed computing environments, ensuring scalability, efficiency, and scientific accuracy.
• Drives the development of innovative data science solutions and formulates strategic data initiatives that align with organizational objectives and competitive priorities.
• Applies deep domain expertise and advanced modeling techniques to integrate complex data from diverse sources, producing actionable insights and solutions for high-impact business and healthcare challenges.
• Leads research and innovation initiatives within the data science community, contributing to open-source projects, developing white papers, and promoting thought leadership through knowledge sharing and collaboration.
• Develops and oversees the creation of technical reports, analytic studies, and quality improvement publications, ensuring accuracy, clarity, and defensibility of methodologies and results.
• Designs and evaluates intervention strategies and re-measurement methodologies to assess the impact of quality improvement initiatives, translating data findings into practical recommendations.
• Collaborates with cross-functional leaders to communicate complex data science results in a clear, actionable manner, aligning analytical outcomes with strategic decision-making and long-term organizational goals.

Level of supervision received: Plans and arranges own work; works with manager to prioritize projects.

Education (can be substituted for experience): Bachelor's Degree required; Master's Degree in Statistics preferred

Work Experience (can be substituted for education): 8 - 11 years required; 12 - 14 years preferred