Guidehouse is looking to solve federal public health problems by leading quantitative analysis and modeling of real-world data, including CMS, commercial claims, and clinical health data, to generate actionable insights.
Requirements
- Strong proficiency in R, Python (including libraries such as Pandas, NumPy, Scikit-learn), and SQL, including large data set manipulation.
- Demonstrated experience with statistical modeling, machine learning, and data visualization.
- Experience with DataBricks and/or Snowflake.
- Experience with generative AI, NLP, or advanced analytics in healthcare settings.
- Deep experience in biostatistics and using statistical platforms including SAS and R
- Familiarity with public health surveillance systems, federal health programs, or similar public sector environments.
- Experience in chronic disease surveillance, preferably neurological conditions
Responsibilities
- Lead quantitative analysis and modeling of real-world data, including CMS, commercial claims, and clinical health data, to generate actionable insights for federal public health.
- Lead analyses to estimate chronic disease population-level prevalence and incidence leveraging real-world data.
- Design, implement, and refine machine learning and statistical models (e.g., regression, clustering, causal inference) for surveillance and research purposes.
- Develop and maintain data pipelines and dashboards for large-scale health datasets using R, Python, and SQL.
- Utilize DataBricks and Snowflake for scalable data processing and analytics.
- Ensure data quality, documentation, and reproducibility across all analytic workflows.
- Prepare scientific reports, presentations, and publications for both technical and non-technical audiences.
Other
- Advanced degree (MS or PhD) in Data Science, Epidemiology, Public Health, Biostatistics, or related field.
- Minimum FIVE (5) years of experience in health data science and epidemiology, including deep experience analyzing CMS or commercial claims data, clinical data, or other large health datasets to generate epidemiological population-level estimates.
- Excellent communication and collaboration skills.
- Ability to work in a fast-paced environment independently to produce high-quality deliverables on-time
- Ability to Obtain Public Trust
