• Design and deliver advanced analytical and machine learning solutions • Develop and deploy machine learning models for financial use cases • Perform exploratory data analysis on structured and unstructured datasets • Design scalable machine learning pipelines • Lead model validation and regulatory compliance • Present insights and recommendations to senior stakeholders

• Own the strategy, execution, and impact of Data Science across product, marketing, and forecasting. • Set direction for how the team supports product development, experimentation, lifecycle, growth, and business decision-making. • Ensure focus on the highest-value problems across Product, Marketing, Care, and B2B, tied to member and business outcomes. • Establish high standards across experimentation, causal inference, modeling, forecasting, segmentation, and statistical rigor. • Raise quality in hypotheses, metrics, experiment design, model evaluation, and decision recommendations. • Build durable review mechanisms and operating standards to ensure work is sound, interpretable, and decision-ready. • Lead product analytics to shape how user behavior is understood across acquisition, engagement, retention, and care journeys. • Strengthen data foundations including instrumentation, telemetry quality, validation, and experimentation readiness. • Partner cross-functionally to define measurement strategies that demonstrate care impact, outcomes, and ROI. • Build and lead a high-performing team by developing leaders, raising the talent bar, and leveraging AI to improve productivity and insight generation.

• Partner with the payments team by translating the business needs to design and develop core tables, build dashboards, define metrics • Perform strategic analysis and research to identify new opportunities where business can be improved • Create data visualizations to translate analytic results for broad understanding across the business • Build scalable automation solutions using SQL, dashboards, and other tools to create leverage for yourself and the payments team

Role Description The Lead Data Scientist independently applies advanced data science and AI (DS/AI) techniques to solve complex problems and drive business outcomes within McGraw Hill’s Higher Education business unit. - Develop innovative methodologies, scalable solutions, and structured frameworks to address ambiguous and complex challenges. - Apply acquired professional knowledge to interpret internal business issues and recommend solutions/best practices in line with business goals. - Identify patterns and trends across diverse problems to propose actionable solutions that address both immediate needs and long-term organizational goals. - Operate with substantial independence, planning and executing projects with minimal oversight while seeking leadership input for strategic alignment. - Foster cross-team collaboration to ensure alignment with organizational priorities and strategic goals. - Communicate technical concepts and insights clearly to diverse audiences, including non-technical stakeholders and cross-functional teams, using data-driven storytelling to influence decisions. Qualifications - Ph.D. or equivalent in Data Science, Applied Mathematics, Statistics, or a related field. - 4–7 years of professional experience with demonstrated ability to deliver impactful projects. - Advanced knowledge in a specialization with an understanding of cross-disciplinary concepts and emerging trends, enabling collaboration across teams and domains. - Deep knowledge and practical experience with production-scale DS/AI systems with a recent focus on generative AI (GenAI). - Understanding of complex GenAI architectures and experience with scaling, monitoring, and maintaining these systems. - Experience supporting DS/AI systems across stages of the Machine Learning Operations/LLM Operations lifecycle at enterprise scale. - Strong technical communication and collaboration skills, particularly communicating with non-technical stakeholders and working collaboratively with engineering teams to meet project goals and timelines. - Strong experience with Python (7+ years). Preferred Experience & Skills - Affinity for education. - Experience with educational data. - Familiarity with AI adoption in higher education. Benefits - The pay range for this position is between $136,000-$190,000 annually; however, base pay offered may vary depending on job-related knowledge, skills, experience, and location. - 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.