APPLIED DATA SCIENTIST REGULATORY AND STATISTICAL
About The Position
Dr. Ciara Freeman at the esteemed Moffitt Cancer Center is on the lookout for a talented Applied Data Scientist - Regulatory & Statistical, to help build the first regulatory-grade AI models that predict therapy response in multiple myeloma. You'll partner with a physician-scientist PI and data-engineering team to prototype, validate, and document predictive models designed for clinical use. This is hands-on translational ML - fast iteration, real impact, auditable results. Your models will form the core of clinically actionable, auditable AI systems that change how we treat cancer. Moffitt Cancer Center proudly stands as a Comprehensive Cancer Center designated by the National Cancer Institute (NCI) in the vibrant city of Tampa, Florida. This dynamic city is an exceptional choice for those seeking exciting opportunities in a rapidly growing metropolitan area. With its flourishing economy and rich cultural diversity, the Tampa Bay region masterfully combines urban elegance with breathtaking natural beauty. Discover why countless individuals have chosen to make Tampa their home and experience firsthand what makes it one of the fastest-growing metropolitan cities in the United States.
Requirements
- Expert in Python (scikit-learn, XGBoost, PyTorch/TensorFlow).
- Skilled in survival or clinical modeling; thrive where rigor meets speed.
- Master's degree in Computer Science, Data Science, Biostatistics, or a related quantitative field with seven (7) years of applied statistical or machine learning model development experience in healthcare, biotech, or regulated environments.
- Or PhD with five (5) years of applied statistical or machine learning model development experience in healthcare, biotech, or regulated environments.
Nice To Haves
- Familiarity with Snowflake or modern data-engineering workflows preferred.
Responsibilities
- Develop and validate multimodal survival and risk-stratification models (clinical + omics + imaging)
- Collaborate with engineers to define and extract features.
- Perform calibration, bias analysis, and explainability (SHAP, PDPs, model cards).
- Translate results into clinician-friendly insights and contribute to IP and regulatory filings.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Industry
Religious, Grantmaking, Civic, Professional, and Similar Organizations
Number of Employees
5,001-10,000 employees
