Collaborate with stakeholders and subject matter experts to define and refine data-driven initiatives that enhance healthcare operations and outcomes. Develop a strong understanding of complex, high-volume, and heterogeneous data, ensuring rigorous data development, cleaning, and validation. Apply machine learning and statistical modeling techniques, including regression, classification, clustering, time series forecasting, and ensemble methods. Utilize LLM-based text analytics and NLP techniques to extract insights from unstructured data sources such as clinical notes and reports. Perform exploratory data analysis and build structured analytical workflows using Python, R, and SQL. Communicate findings and methodologies effectively to both technical and non-technical audiences through reports, presentations, and interactive visualizations. Independently manage projects, setting clear objectives, benchmarks, and milestones while balancing iterative development with accountability. Develop well-documented, reusable code on cloud computing platforms to support analytical pipelines. Follow best practices in collaborative software development, including version control (Git) and modular code design.
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Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
11-50 employees