Progyny, Inc.

Vice President – Machine Learning

Progyny, Inc.

full-time

Posted on:

Origin:  • 🇺🇸 United States • New York

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Salary

💰 $210,000 - $220,000 per year

Job Level

Lead

Tech Stack

CognosPandasPythonPyTorchSQLTableauTensorflow

About the role

  • Lead a team of data scientists and participate in development and expansion of applied ML methods to analyze member program engagement and support optimization opportunities
  • Support the strategic vision for ML and related data science initiatives to analyze member behavior patterns associated with effective outcomes
  • Work with third-party and in-house models to balance build vs buy decisions for near-term progress and long-term capability
  • Collaborate with Emerging Technologies Engineering to build infrastructure for design, serving, deployment, and monitoring of train/test/deploy processes
  • Evaluate and incorporate various sources of member engagement data (call transcripts, interaction history, user analytics, raw financial data) to produce comprehensive member population trends
  • Assist with member segmentation/persona development and inform marketing, call center, digital experience, and other operational functions
  • Present complex analytical insights to stakeholders in an easy-to-understand and actionable way

Requirements

  • 10+ years of data science experience with a clear and demonstrated focus on healthcare population analytics using scalable analytical engines / machine learning models
  • Graduate degree in a quantitative scientific discipline required
  • Experience leading research functions and evaluating the likelihood of meaningful discovery vs allocation of resources
  • Semantic analysis, NLP, or other experience with free text assessment required; deep understanding of prompt structures preferred when working with commercial models
  • Demonstrable expertise with Python required; experience with common data science and ML libraries (PyTorch, Tensorflow, or similar, as well as standard libraries like Pandas, scikit-learn, etc.)
  • Proven experience in evaluation and application of existing analytic models/methods to adjacent business use cases
  • Demonstrable proficiency with relational and graph-based data models and query vocabulary (SQL, Cypher, etc.)
  • Proven experience with healthcare data and terminology/ontology standards (ex: FHIR, Snomed, etc.)
  • Experience in MLOps lifecycle and tools required for training, deployment, and testing loop of analytic models
  • Prior experience with data visualization tools (e.g. Power BI, Cognos, Tableau, Looker) preferred
  • Enjoys learning, dissecting, optimizing, and ultimately owning existing modelling methodologies
  • Organized and methodical with very strong attention to detail
  • Demonstrated ability to be adaptive and inquisitive; natural problem solver
  • Ability to work autonomously with minimal direction on multiple endeavors at once
  • Driven to deliver results with the ability to establish rapport, earn trust, and effectively collaborate with others