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Director, Analytics and Data Science

Job in New York, New York County, New York, 10007, USA
Listing for: Institute of International Education
Full Time position
Listed on 2026-08-21
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 180000 - 230000 USD Yearly USD 180000.00 230000.00 YEAR
Job Description & How to Apply Below
Location: New York

The Director, Analytics and Data Science at Institute of International Education will lead the Data Science & AI function to advance data-driven decision making across Educational Services programs. You will define analytics strategy, oversee data science roadmaps, and deliver cloud-based, production-grade models that enhance learner outcomes and operational efficiency. Partnering with cross-functional leaders, you'll translate complex insights into actionable recommendations, champion data governance, and mentor a high-performing analytics team in a fast-paced, innovative, and collaborative environment.

Responsibilities

  • Define and execute the analytics and data science strategy for Educational Services programs.
  • Lead and mentor a high-performing data science and analytics team.
  • Design and oversee development of cloud-based analytics products and predictive models.
  • Collaborate with cross-functional leaders to embed analytics into decision making.
  • Establish and enforce best practices for data governance, quality, and security.
  • Translate complex analytical insights into clear, actionable recommendations for stakeholders.
  • Drive experimentation, A/B testing, and measurement frameworks for key initiatives.
  • Partner with engineering teams to product ionize and scale data science solutions.
  • Monitor model performance and ensure ethical, responsible AI practices.
  • Foster a culture of innovation, collaboration, and continuous learning in analytics.

Required Skills

  • Statistical modeling
  • Machine learning
  • Data engineering for analytics
  • SQLPython or RCloud computing (AWS, Azure, or GCP)
  • Data visualization (Tableau, Power BI, or similar)
  • MLOps and model deployment
  • Data governance and privacy
  • Experimentation and A/B testing
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