Data Scientist - San Diego
The Data Scientist at Confidential Client provides advanced analytics and develops statistical, machine learning, and AI models to support clinical, operational, and business objectives. This hybrid role involves managing large healthcare datasets, partnering with stakeholders to drive data-driven decisions, and operationalizing innovative AI solutions to improve outcomes and performance within the San Diego area.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Hospitals and Health Care.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Overview
Confidential Client (Hospitals and Health Care) is seeking a Data Scientist to deliver advanced analytics, machine learning, and AI solutions that improve clinical, operational, and business outcomes. This is a benefited, full-time role with mostly-remote work and an occasional on-site presence required; candidates must reside in the San Diego, CA area.
What You’ll Do
- Provide advanced, integrated analytics to support organizational goals across clinical, operational, and financial domains.
- Source, clean, and analyze large and unstructured healthcare datasets (claims, authorizations, pharmacy, provider, membership).
- Design and implement data models, statistical analyses, predictive models, and machine learning solutions.
- Develop, evaluate, and operationalize AI and ML solutions — including generative AI — following responsible, measurable practices.
- Partner with clinical, operational, and business stakeholders to translate requirements into actionable analytics and production-ready solutions.
- Communicate findings and recommendations clearly to technical and non-technical audiences; create dashboards and reports using Power BI or Tableau.
- Evaluate emerging AI/ML tools and technologies and recommend practical adoption pathways.
Qualifications
Required
- Bachelor’s degree in a quantitative field or equivalent experience.
- Experience with healthcare data sources (medical claims, authorizations, pharmacy, provider, membership).
- Experience in statistical modeling and interpreting complex datasets.
- Experience analyzing medical expenses & utilization trends, RAF scores, comorbidities/disease burden, or healthcare quality measures.
- Proficiency in R, Python, or SAS.
- Intermediate SQL skills and familiarity with ETL, data modeling, and reporting tools.
- Experience with Power BI or Tableau.
- Strong critical thinking, written and verbal communication, and customer-service skills.
- Ability to work independently and collaboratively, and to explain complex concepts to leadership.
Preferred
- Master’s degree in Data Science, Quantitative, Clinical, or Engineering field.
- Experience with financial datasets (accounting, health plan claims, P&L) and market/financial projections.
- Prior experience working with Epic data structures and reporting environments.
- Experience leading analytics for value-based populations and predictive modeling for clinical intelligence.
Compensation
- Pay Range: $51.66 - $74.92 per hour (hourly range provided by the confidential client). Pay decisions consider experience, qualifications, and local laws.
Why This Role
- Join a large healthcare organization committed to quality, learning, and continuous improvement.
- Work on high-impact analytics projects that directly affect patient care and business performance.
- Access to comprehensive benefits including health, wellness, career development, and retirement options.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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