Director Analytics- Data Science 

Position Summary

The Director of Data Science leads our data science function, overseeing the development of cutting-edge models, algorithms, and data products that power decision-making and innovation across NewYork-Presbyterian, Weill Cornell Medicine, and Columbia. The director consults with tri-institutional senior administrative and clinical leaders to define information requirements, data science services, and deliverables to meet the needs of the enterprise. The director defines the Data Shared Service data science strategy, leads teams to build AI/ML models, and translates data insights into actionable strategies for clinical, operational, and business improvements. Key responsibilities include developing scalable analytics, ensuring regulatory compliance (like HIPAA), and communicating complex findings to stakeholders to drive innovation and better patient outcomes. The director will collaborate proactively with internal and external analytics teams, data engineering teams, vendors, and other IT departments to support data-driven initiatives. The director will oversee the responsible and effective use of various proprietary and non-proprietary data sets, including individual patient and employee data, assuming adherence to all regulatory and accreditation requirements. The director will have supervisory responsibilities, advising and guiding the work of individual team members, identifying and coordinating strategies across teams, and managing and mentoring staff.

Essential Job Duties

Strategic Leadership:

•  Develop a comprehensive data science roadmap aligned with healthcare business goals—e.g., population health management, clinical risk prediction, cost containment, and patient engagement.
• Identify strategic opportunities to apply AI/ML in domains such as: Predictive analytics (e.g., readmission risk, disease progression), Clinical decision support, Natural language processing of clinical notes (NLP), Claims and billing fraud detection, Patient segmentation for care management, Operational efficiency (e.g., staffing, appointment optimization)

Team & Capability Building:

• Hire, lead, and mentor a multidisciplinary team of data scientists, clinical informaticists, and ML engineers.
• Create training pathways that combine machine learning and clinical domain knowledge.
• • Foster a culture of collaboration between technical, clinical, and operational stakeholders.

Healthcare-Specific Technical Oversight:

• Guide the development of machine learning and statistical models trained on complex healthcare datasets, including: EHRs (Electronic Health Records),   Patient-reported outcomes,Genomic and imaging data (if applicable)
• Lead efforts in model validation, clinical interpretability, and bias mitigation.
• Collaborate with clinical and compliance teams to ensure models meet standards for fairness, accountability, and transparency.

Cross-Functional Collaboration:

• Work closely with product, engineering, clinical, operations, and compliance teams to co-design AI-driven products and workflows.
• Ensure that AI/ML solutions integrate smoothly into clinician and patient-facing systems (e.g., EMR platforms, patient portals).

Regulatory & Ethical Compliance:

• Ensure all analytics initiatives comply with HIPAA, HITECH, and GDPR (if applicable).
• Advocate for ethical AI practices in healthcare—addressing bias, explainability, and patient trust.
• Oversee appropriate PHI handling, de-identification, and data access protocols.
• Responsible for the recruitment, selection, and orientation of employees in assigned areas. Provides work direction, assigns and/or schedules work, conducts on-the-job training, and answers job-related questions. Monitors performance and adherence to attendance policies. Prepares performance evaluations and recommends appropriate personnel actions for staff, relative to promotions, transfers, and disciplinary action up to and including termination, according to hospital policies and procedures. Assists in the interpretation, development, and implementation of hospital personnel and departmental policies and procedures.
• Represent the enterprise at professional association meetings, periodically serving on advisory groups and committees.
• Investigate, evaluate, and implement any new technologies that may effectively and more efficiently meet departmental and organizational goals.
• Performs other special projects and duties as assigned.

Preferred Qualifications:

Education:

• MS or PhD in Computer Science, Biomedical Informatics, Statistics, Engineering, or related quantitative field.
• Additional training in health informatics, epidemiology, or biostatistics is a strong plus.

Experience:

• 8+ years in data science or machine learning roles, with 3+ years in a leadership position.
• 4+ years working with healthcare data (EHRs, claims, registries, SDOH, etc.).
• Experience delivering ML models in clinical or healthcare operations settings.
• Familiarity with clinical vocabularies and standards such as ICD-10, SNOMED CT, LOINC, HL7/FHIR.
• Strong experience working in or with healthcare organizations (e.g., payers, providers, health tech, pharma, public health).

Technical Skills:

• Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow), R, and SQL.
• Experience with big data tools (Spark, Snowflake) and cloud platforms (AWS, GCP, Azure Health Data Services).
• Familiarity with healthcare data tools and platforms such as OMOP/OHDSI, Epic
• Hands-on with NLP tools (e.g., spaCy, transformers, cTAKES, MedSpaCy) for unstructured clinical text.

Required Qualifications:

• Bachelor's Degree
• Minimum ten years of previous work related experience

“Requires on-site presence, four days a week; therefore, should live within a commutable distance.  No relocation assistance available.”

Join a healthcare system where employee engagement is at an all-time high. Here we foster a culture of respect, belonging, and inclusion. Enjoy comprehensive and competitive benefits that support you and your family in every aspect of life. Start your life-changing journey today.

Please note that all roles require on-site presence (variable by role). Therefore, all employees should live within a commutable distance to NYP.

NYP will not reimburse for travel expenses.

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• 2024 “Great Place To Work Certified”
• 2024 “America’s Best Large Employers” – Forbes
• 2024 “Best Places to Work in IT” – Computerworld
• 2023 “Best Employers for Women” – Forbes
• 2023 “Workplace Well-being Platinum Winner” – Aetna
• 2023 “America’s Best-In-State Employers” – Forbes
• “Silver HCM Excellence Award for Learning & Development” – Brandon Hall Group

NewYork-Presbyterian Hospital is an equal opportunity employer.

Salary Range:

It all begins with you. Our amazing compensation packages start with competitive base pay and include recognition for your experience, education, and licensure. Then we add our amazing benefits, countless opportunities for personal and professional growth and a dynamic environment that embraces every person. Join our team and discover where amazing works.