Senior Director, Data Development
V
Verana HealthDigital health
Employees work remotely in AZ, CA, CO, CT, FL, GA, IL, LA, MA, MN, NC, NJ, NV, NY, OH, PA, SC, TN, TX, VA, WA, D.C.Full-TimeDirector
Salary$245,000 - $275,000 (A geographic premium may be applied to base salary)
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Job Details
- Experience
- 10+ years of experience applying machine learning to clinical or healthcare datasets; 5+ years managing technical teams
- Required Skills
- PythonSQLMachine LearningMLFlowDatabricksREHRPySpark
Requirements
- Master’s or doctorate in a quantitative discipline (e.g., data science, computer science, machine learning, biostatistics, biomedical informatics).
- 10+ years of experience applying machine learning to clinical or healthcare datasets.
- Recent experience deploying, fine-tuning, evaluating, or operationalizing foundation models.
- 5+ years managing technical teams.
- Strong programming experience using Python, SQL, PySpark, R, or similar tools.
- Experience working within modern cloud-based machine learning ecosystems (e.g., Databricks, SageMaker, MLflow).
- Experience moving machine learning systems from experimentation into production environments.
- Familiarity with machine learning approaches for clinical imaging data.
- Experience working with clinical datasets derived from EHR systems.
- Clear communication skills and ability to deliver presentations to executive teams.
- Ability to work effectively with cross-functional teams to inform data product roadmaps.
Responsibilities
- Lead a team developing and operationalizing machine learning solutions for structured and unstructured healthcare data, including clinical text and imaging workflows.
- Guide the evaluation, fine-tuning, deployment, and monitoring of pretrained language models for healthcare applications.
- Define technical strategy and development priorities for machine learning capabilities supporting data products.
- Establish best practices for model lifecycle management, validation, reproducibility, explainability, and documentation.
- Partner cross-functionally with Product, Engineering, Medical, and Commercial teams to align technical solutions with scientific and business objectives.
- Drive high standards for data quality, model governance, and clinical relevance in production data products.
- Mentor and develop machine learning scientists and technical leaders.
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