Senior Director, Data Development

Verana Health•San Francisco, NY

1d•Hybrid

About The Position

Verana Health is a digital health company focused on delivering quality drug lifecycle and medical practice insights from a real-world data network. The company recently secured significant funding and is driven by its DRIVE values: Diversity, Responsibility, Integrity, Voice-of-Customer, and End-Results. Verana Health operates with a hybrid work model for employees in specific locations and requires permanent residency in certain states. This role involves leading the application of machine learning to transform clinical data into scalable healthcare data products, reporting to the Chief Data & Science Officer. The team utilizes structured and unstructured electronic health record (EHR) data, including clinical text and imaging, to support Verana Qdata® products and generate real-world insights. The position requires a blend of technical leadership, team development, and cross-functional collaboration to ensure data products meet quality and fit-for-purpose requirements, with a focus on validation, explainability, and scientific quality. The Data & Science team aims to improve patient care through the use of real-world clinical data, machine learning, and clinical expertise.

Requirements

Master’s or doctorate in a quantitative discipline (e.g., data science, computer science, machine learning, biostatistics, biomedical informatics, etc.)
10+ years of experience applying machine learning to clinical or healthcare datasets, including recent experience deploying, fine-tuning, evaluating, or operationalizing foundation models and applied machine learning systems.
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 and deployment environments (e.g., Databricks, SageMaker, MLflow, distributed compute platforms, or similar tooling).
Experience moving machine learning systems from experimentation into production environments, including model evaluation, monitoring, performance optimization, and cross-functional operationalization.
Familiarity with machine learning approaches for clinical imaging data.
Experience working with clinical datasets derived from EHR systems and related healthcare data sources.
Clear communication skills and able to deliver internal/external presentations, particularly to executive teams.
Ability to work effectively with cross-functional teams, including to inform data product roadmap.
Ability to prioritize and manage multiple initiatives with high attention to detail.
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Nice To Haves

Candidates based in the Bay Area, New York City, and Knoxville, Tennessee will be give priority consideration.
Candidates who are willing to relocate are also encouraged to apply.

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.
Help define technical strategy and development priorities for machine learning capabilities supporting Verana’s 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 across the organization.