Omada Health is seeking a Senior Data Analyst to advance their mission of delivering high-quality, equitable healthcare through data-driven insights and innovation, setting a new standard for quality and equity in digital health by applying advanced analytical expertise to solve complex problems of diverse scope.
Requirements
- Expert SQL skills and proficiency in additional programming languages (Python or R preferred).
- Advanced knowledge of BI tools and data visualization, especially Tableau, including development, server management, and best practices.
- Strong grasp of data management principles, governance frameworks, and data architecture design.
- Experience with advanced statistical methods to identify patterns, correlations, and predictive models.
- Experience analyzing data related to clinical outcomes, equity metrics, or quality improvement initiatives, ideally within digital health, health plans, or employer benefits programs.
- Experience with clinical quality measurement frameworks, including HEDIS, STAR ratings, and other healthcare performance evaluation systems.
- Familiarity with leveraging AI technologies (e.g., machine learning, natural language processing) to enhance clinical quality initiatives, such as predictive modeling for patient outcomes or automated quality metric reporting.
Responsibilities
- Generate actionable insights, build intuitive dashboards, define and refine quality metrics, and influence strategies that improve member behavior to improve clinical outcomes.
- Utilize population health approaches and data analytics to develop informed and targeted interventions that identify individuals for engagement based on their health needs and risk factors.
- Oversee the development of dashboards and visualizations that communicate the impact of clinical programs on health outcomes and operational efficiency.
- Identify and refine performance metrics that align with strategic goals and demonstrate program value to members and stakeholders.
- Champion the adoption of self-service analytics among care teams and stakeholders, enabling data-informed decision-making and innovative strategies to improve member outcomes.
- Lead analytical efforts to support healthcare accreditation submissions (e.g., NCQA, DPP, URAC) and ensure ongoing compliance with quality standards.
- Apply statistical methods and machine learning models to identify patterns, correlations, and predictive insights for personalized care and patient risk stratification.
Other
- 7+ years in analytics, preferably in healthcare, digital health, or a related field.
- Strong organizational skills and attention to detail.
- Clear, concise written and verbal communication.
- Ability to manage multiple priorities and work independently.
- Eagerness to collaborate and learn from diverse perspectives.
