Data Scientist - San Diego

This is a benefited, full-time position working mostly remote with the requirement of occasionally coming on-site. Although remote, this individual must reside within the San Diego area. You will enjoy comprehensive benefits that cover health & wellness, career development, and retirement options among other benefits.

At Scripps Health, you will experience the pride, support, and respect that has been repeatedly recognized as one of the nation’s Top 100 Places to Work.

You will thrive in an environment where team members are engaged and committed to providing excellent care and making a difference in the lives of their patients and their teammates So, if you’re open to change, go ahead and unlock your potential.

Why join Scripps Health?

At Scripps Health, your ambition is empowered and your abilities are appreciated:

• Nearly a quarter of our employees have been with Scripps Health for over 10 years.
• Scripps is a Great Place to Work Certified company for 2025.
• Scripps Health has been consistently ranked as a top employer for women, millennials, diversity, and as an overall workplace by various national publications.
• Becker's Healthcare ranked Scripps Health on its 2026 list of 150 top places to work in health care.
• We have transitional and professional development programs to create a learning environment that enables you to thrive in your specific field as well as in your overall career.
• Our specialties have been nationally recognized for quality in areas such as cardiovascular care, oncology, orthopedics, geriatrics, obstetrics and gynecology, and gastroenterology.

As a Data Scientist, you will:

• Provide advanced, integrated analytics in support of organizational objectives.
• Source, manage, and analyze large amounts of unstructured data; synthesize and communicate results to facilitate data-driven decision making.
• Partner with internal and external constituents to understand key requirements, plan and execute projects, and produce actionable data to support strategic initiatives and drive continuous performance improvement.
• Design data modeling processes and develop statistical, machine learning, and predictive models to generate actionable insights for clinical, operational, and business stakeholders.
• The right candidate will have a passion for discovering solutions hidden in large data sets and working with customers to improve outcomes and performance.
• Develop, evaluate, and operationalize AI and machine learning solutions, including generative AI, to address clinical, operational, and business needs.
• Evaluate emerging AI technologies and tools, partnering with technical and business stakeholders to translate new capabilities into practical, responsible, and measurable solutions.

Required Qualifications:

• Bachelor's degree.
• Experience with different healthcare data sources (medical claims, authorizations, pharmacy, provider, membership).
• Experience with statistical modeling and interpretations of complex data.
• Experience in analyzing any of the following: Medical expenses & utilization trends, RAF Scores, Comorbidities & disease burden, Healthcare quality measures.
• Excellent critical and analytical thinking, customer service skills, and strong written and verbal communication skills.
• Experience in R, Python, or SAS programming.
• Intermediate knowledge of SQL, ETL, data modeling, and reporting technologies.
• Intermediate knowledge of Power BI or Tableau.
• Must have knowledge and skills necessary to explain complex concepts to team members and leadership.
• Ability to work both independently and collaboratively as part of a team.

Preferred Qualifications:

• Master's Degree in related field (Data Science, Quantitative, Clinical, or Engineering).
• Experience in working with financial datasets (e.g., accounting, health plan claims, P&L).
• Prior experience with Epic data structures and reporting environments.
• Expertise in leading analytics for value-based populations.
• Experience in predictive modeling for clinical intelligence.
• Experience in market intelligence and financial projections.