The Clinical Data Scientist II supports Enterprise Analytics by performing complex healthcare data analyses and delivering clear, actionable insights to leaders. This role requires strong technical skills and healthcare knowledge and operates with moderate supervision, receiving guidance on priorities, scope, and approach while independently executing assigned work.
Essential Job Functions:
Data Analysis & Insights
- Perform advanced data analysis to identify trends, cost drivers, and improvement opportunities.
- Analyze structured and unstructured data to address complex clinical, financial, and operational questions.
- Develop insights and recommendations that support enterprise performance and organizational priorities.
- Conduct ad hoc data mining and analyses to support business needs.
Collaboration & Execution
- Serve as an analytics point of contact for assigned subject areas, with guidance as needed.
- Work closely with clinical, operations, finance, and product teams to define problems and deliver analytical solutions.
- Execute analytics projects independently after initial direction is provided.
- Seek input and feedback to ensure alignment with analytical standards and expectations.
Reporting & Visualization
- Develop, maintain, and enhance dashboards and automated reports using Tableau, Sigma, or similar tools.
- Produce clear trend reports and performance analyses for leadership review.
- Validate data outputs, troubleshoot reporting issues, and improve reporting accuracy and efficiency.
Communication
- Clearly communicate findings and recommendations to technical and non-technical stakeholders.
- Present insights to leadership and market leaders in a clear, practical manner.
- Adjust messaging based on audience and context.
Other Job Functions:
- Follow company policies and procedures.
- Provide responsive and professional internal customer service.
- Communicate clearly and effectively in written and verbal interactions.
- Set and complete goals with guidance and feedback from leadership.
Required Qualifications:
Minimum Experience
- Bachelor’s degree in Mathematics, Statistics, Public Health (MPH), or a related field.
- Minimum of 4 years of experience in data science or analytics, preferably in healthcare.
- Experience working with large, complex datasets and data lake environments.
- Experience with claims data, CMS files, and trend analysis strongly preferred.
Skills & Abilities
- Strong experience with healthcare analytics methods such as episode groupers and risk stratification.
- Proficiency in SQL and analytical tools such as SAS, R, or Python.
- Advanced experience with Excel and data visualization tools (Tableau, Sigma, or similar).
- Strong understanding of medical claims, clinical, and quality data.
- Ability to manage multiple priorities and meet deadlines with guidance.
- Strong analytical, statistical, and problem-solving skills.
- Clear written and verbal communication skills.
Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.
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What We Do
agilon health is transforming health care for seniors by empowering primary-care physicians to focus on the entire health of their patients. Through our platform and partnership model, agilon health is leading the nation in creating the system we need – one built on the value of care, not the volume of fees. We honor the independence of local physicians and serve as their long-term partner so they can be the physicians they trained to be. agilon is built for physicians by physicians, as the patient-physician relationship is the cornerstone of care. We allow primary care physicians to take the long view of their relationships with patients, and to be confident in the long-term financial viability of their own practices. We do this through a Total Care Model that maintains the independence of physicians; unites them in a network of like-minded leaders; and integrates all of the components of a global risk business model into a single platform.
