Data Science Director
United StatesFull-TimeDirector
Salary178,500 - 297,500 USD per year
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Job Details
- Experience
- 8+ years of experience in data science, advanced analytics, or machine learning roles; 5+ years of leadership experience managing data science or AI teams.
- Required Skills
- PythonSQLMachine LearningAzureSparkDatabricksDeep LearningNLPGenerative AI
Requirements
- 8+ years of experience in data science, advanced analytics, or machine learning roles.
- 5+ years of leadership experience managing data science or AI teams in production environments.
- Proven track record of deploying machine learning or generative AI solutions in regulated or complex industries, preferably healthcare.
- Strong expertise in machine learning, deep learning, NLP, and generative AI methodologies.
- Hands-on experience with cloud data platforms such as Azure or Databricks and modern data engineering practices.
- Advanced programming skills in Python, SQL, Linux, and familiarity with distributed systems such as Spark or Hadoop.
- Experience building scalable AI pipelines, data infrastructure, and production-grade analytics systems.
- Strong executive presence with the ability to influence cross-functional and senior stakeholders.
- Ability to translate technical concepts into clear business and clinical insights.
- Familiarity with healthcare data standards such as HL7 FHIR is a strong advantage.
Responsibilities
- Lead the end-to-end strategy, development, and execution of AI/ML and data science initiatives supporting clinical and operational decision-making.
- Own the lifecycle of predictive models, deep learning systems, and generative AI solutions, including validation, deployment, monitoring, and continuous improvement.
- Design and scale intelligent automation systems, including prior authorization optimization and real-time clinical decision support tools.
- Build and modernize enterprise data infrastructure, including cloud-based lakehouse architectures and scalable analytics platforms.
- Develop integrated data pipelines combining clinical, operational, and administrative datasets to enable advanced analytics and AI use cases.
- Establish frameworks for model governance, explainability, validation, and regulatory compliance in a healthcare environment.
- Partner with clinical and operational leaders to ensure AI solutions align with evidence-based care pathways and improve outcomes.
- Lead and grow a high-performing data science organization, fostering innovation, accountability, and technical excellence.
- Translate complex analytical outputs into actionable insights for executive, clinical, and technical stakeholders.
- Evaluate and implement emerging AI approaches, including LLMs, retrieval-augmented generation, and agentic workflows.
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