Senior Health Data Scientist leading complex data extraction and modeling for healthcare solutions at Inovalon. Collaborating with multidisciplinary teams to deliver data - driven insights.
About the role
- Data Scientist developing machine learning solutions and delivering insights for operational decisions. Collaborating with stakeholders to apply analytical techniques and improve business outcomes.
Responsibilities
- Work directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, formulate the right analytical questions, and translate business challenges into rigorous data science approaches.
- Apply deep analytical thinking to decompose complex problems—critically evaluate data quality and relevance, challenge assumptions, and design methods that address the business need.
- Develop statistical models, machine learning solutions, and analytical frameworks that deliver actionable insights and drive operational decisions.
- Build user‑friendly, production‑grade ML/AI applications (e.g., Streamlit, Dash) and analytical artifacts that provide data insights to teams across the enterprise and enable better decision making.
- Write production-quality Python code and develop analytical pipelines using cloud-based platforms (AWS, Databricks) to support scalable and reproducible data science workflows.
- Deliver insights through multiple channels—executive recommendations, analytical reports, interactive dashboards, and direct consultation with business leaders.
- Take ownership of the technical quality and business impact of your work—make thoughtful methodological decisions, validate approaches rigorously, and stand behind your recommendations.
- Stay current on analytical methods, statistical techniques, and domain-specific best practices to continuously improve the quality and impact of your work.
Requirements
- Bachelor’s degree with 5+ years of relevant professional experience in data science or data analysis – OR – Master’s degree with 3+ years of relevant professional experience in data science or data analysis.
- Proficiency with Python, SQL, and Git.
- Deep understanding of statistical methods, machine learning algorithms, and when to apply different analytical techniques.
- Experience developing and deploying machine learning models in production environments.
- Proven ability to translate complex business problems into rigorous analytical frameworks.
- Demonstrated problem‑solving and critical‑thinking skills with an ability to handle complex analytical challenges.
- Excellent communication skills and ability to deliver compelling, actionable recommendations to non‑technical stakeholders.
- Strong track record of ownership and accountability for technical decisions and project outcomes.
Benefits
- Health insurance coverage
- Life and disability insurance
- Savings plan
- Company paid holidays
- Paid time off (PTO) for vacation and/or personal business
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