Sr Director, Applied Insights

Overview

Build the Future
:
At McGraw Hill, we are dedicated to delivering digital learning experiences that transform education for learners and educators. Our focus is on creating seamless, impactful products that truly benefit our users while supporting growth and collaboration across teams. We foster a culture that values innovation, teamwork, and a balance between career growth and personal well‑being.

The Senior Director, Applied Insights leads the delivery of applied data science and machine learning solutions that generate actionable business insights and measurable business impact across McGraw Hill’s business units. For example, this role will use data to segment users and customers to enable improved engagement, implement data quality AI agents to improve data quality, use sales history to perform churn analysis to better retain customers, and other prioritized solutions.

Reporting to the VP of Data & Analytics, this role partners closely with Analytics Delivery Leads and business leaders to identify, prioritize, and solve high-impact, BU-specific problems using advanced analytics, statistical modeling, and machine learning.

This role blends strategic consulting, hands‑on data science leadership, and business-facing storytelling. The Sr. Director, Applied Insights must understand business strategy, sales, operations, and marketing while also guiding teams through model development, validation, and operationalization. Success requires deep collaboration across BU Leadership, Sales, Marketing, Data Science and AI, Data & Analytics, Global Technology Solution and Customer Success to translate complex data into insights that drive adoption, efficacy, growth, and operational efficiency.

This is a remote position open to applicants authorized to work for any employer within the United States.

• BU-Specific Data Science Consulting
  . Partner with Analytics Delivery Leads and BU leaders to identify internally facing data science needs and opportunities; translate business questions into well-scoped analytical and machine learning use cases aligned to BU priorities.
• Data Science & Machine Learning Delivery. Design, develop, and deploy predictive, prescriptive, and explanatory models that deliver unique insights and measurable business impact. In addition to personally building solutions, partner with data scientists in our Data Science and AI org to increase the impact and throughput of high‑impact solutions.
• Applied Insights Strategy & Roadmap. Define and own the Applied Insights roadmap, balancing short‑term business needs with long‑term analytical capabilities; ensure alignment with enterprise Data & Analytics strategy.
• Advanced Analytics for Growth & Operations. Apply statistical analysis, machine learning, and third‑party data to support market analysis, customer segmentation, demand forecasting, pilot evaluation, and operational planning.
• Cross-Functional Leadership & Influence. Collaborate with Product, Engineering, Sales, Marketing, Customer Support, and Research teams to ensure insights are actionable, trusted, and embedded into decision‑making. This includes tight collaboration within Data & Analytics for appropriate feature engineering.
• Team Leadership. Lead cross‑functional and matrixed data scientists; foster a culture of curiosity, rigor, experimentation, and business impact. Please note this job description is designed to cover the primary duties of the role, but incumbents may be assigned other duties. Duties, responsibilities, and activities may change at any time with or without notice.

• Bachelor’s degree in a quantitative or related field (e.g., Data Science, Statistics, Mathematics, Computer Science) or equivalent experience.
• Master’s degree or PhD preferred.
• 10+ years of progressive experience in data science, advanced analytics, or machine learning roles, including leadership experience.
• Proven experience delivering applied data science and machine learning solutions that improve business outcomes.
• Strong background in statistical modeling, predictive analytics, and machine learning techniques.
• Familiarity with modern data platforms,…