Senior Director, Data Development (Machine Learning)

Location: Remote within approved U.S. states; hybrid work with 3 days per week in the office is required for candidates based in the Bay Area, New York City, or Knoxville. Employees must have permanent residency in Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Louisiana, Massachusetts, Minnesota, North Carolina, New Jersey, Nevada, New York, Ohio, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, or Washington. Candidates must be legally authorized to work in the United States.

Salary: $245,000–$275,000 USD annually; a geographic premium may apply.

Company

hirify.global is a digital health company using real-world clinical data, machine learning, and physician expertise to develop healthcare insights and products across oncology, ophthalmology, neurology, and urology.

What you will do

• Lead a team developing and operationalizing machine learning solutions for structured and unstructured healthcare data, including clinical text and imaging.
• 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 with Product, Engineering, Medical, and Commercial teams to align technical solutions with scientific and business objectives.
• Drive data quality, model governance, clinical relevance, and technical leadership development across the organization.

Requirements

• Master’s degree or doctorate in data science, computer science, machine learning, biostatistics, biomedical informatics, or a related quantitative discipline.
• 10+ years of experience applying machine learning to clinical or healthcare datasets, including experience with foundation models and applied machine learning systems.
• 5+ years of experience managing technical teams.
• Strong programming experience with Python, SQL, PySpark, R, or similar tools.
• Experience with cloud-based machine learning ecosystems and deployment environments such as Databricks, SageMaker, MLflow, or distributed compute platforms.
• Experience moving machine learning systems into production, including evaluation, monitoring, performance optimization, and operationalization.

Nice to have

• Experience with machine learning approaches for clinical imaging data.
• Experience working with EHR-derived clinical datasets and related healthcare data sources.
• Experience presenting technical work to executive audiences.
• Strong cross-functional prioritization and communication skills.

Culture & Benefits

• Inclusive environment focused on diversity, responsibility, integrity, customer voice, and results.
• Medical, dental, and vision insurance plans.
• 401(k) match.
• Flexible time off and paid parental leave.
• Annual learning and wellness stipend.