Sr Director, Applied Insights

McGraw Hill LLC. • UNAVAILABLE, UNAVAILABLE

3d • Remote

About The Position

The Senior Director, Applied Insights leads the delivery of applied data science and machine learning solutions that generate actionable business insights generating measurable business impact across McGraw Hill’s business units. 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, & 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.

Requirements

• Bachelor’s degree in a quantitative or related field (e.g., Data Science, Statistics, Mathematics, Computer Science) or equivalent experience
• 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, cloud-based analytics, and model operationalization.
• Experience translating ambiguous business problems into analytical frameworks and production-ready models.
• Ability to communicate complex analytical insights clearly to executive and non-technical audiences.
• Experience partnering cross-functionally with product, sales, marketing, and operations teams.
• Demonstrated people leadership experience building and managing high-performing technical teams.
• Close familiarity with data and data management practices, including an understanding of the challenges faced by a SaaS organization when dealing with data.
• Ability to understand the big picture and clearly articulate a holistic vision in a range of stakeholder contexts.
• Ability to influence leaders across the enterprise and build consensus.

Nice To Haves

• Master’s degree or PhD preferred
• Experience developing customer segmentation, demand forecasting, or usage-based predictive models.
• Experience working with education data and understanding its unique challenges (e.g., efficacy, adoption, longitudinal analysis).
• Experience and perspective on leveraging agentic AI to supplement existing data to increase intelligence.

Responsibilities

• 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, development, and deployment of 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 solution.
• 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.

Benefits

• An annual bonus plan may be provided as part of the compensation package, in addition to a full range of medical and/or other benefits, depending on the position offered.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior