Data Scientist

NewYork-Presbyterian Hospital

9d • $74,000 - $111,000 • Onsite

About The Position

The Data Scientist builds, validates, and supports the deployment of models for defined business problems. This role works closely with stakeholders to ensure models are safe, interpretable, and aligned with organizational goals, and operates with increasing independence across the full modeling lifecycle.

Requirements

• Bachelor’s or Master’s degree in a quantitative field (or equivalent experience)
• Strong Python/R programming and SQL skills
• 3+ years of experience building and validating ML models
• Experience with ML pipelines and experiment tracking
• Working knowledge of HIPAA and PHI handling requirements
• Strong documentation practices and commitment to reproducibility

Nice To Haves

• Experience with NLP (including transformers), time-series, or survival analysis
• Experience with machine learning in cloud infrastructure or platforms (Azure, Google, AWS etc)
• Strong experience analyzing and deriving insights from complex healthcare data, including EHR and claims.

Responsibilities

• Engineer high-quality features and train, validate, and iterate on ML models
• Conduct error analysis, fairness checks, and bias detection
• Package models for deployment in collaboration with MLOps teams
• Monitor model performance in production and respond to drift
• Translate stakeholder needs into measurable modeling requirements
• Document modeling decisions and maintain reproducible workflows
• Collaborate across teams to ensure models drive meaningful outcomes
• Performs other special projects and duties as assigned.

Benefits

• Comprehensive and competitive benefits that support you and your family in every aspect of life
• Amazing compensation packages start with competitive base pay and include recognition for your experience, education, and licensure
• Amazing benefits
• Countless opportunities for personal and professional growth
• Dynamic environment that embraces every person

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree