Manager, Supply Chain Data Analytics

McGraw Hill LLC.

4d•$108,175 - $125,000•Remote

About The Position

At McGraw Hill we create best-in-class, next-generation learning platforms that are used by millions of students and educators worldwide from kindergarten through graduate school. Our goal is to accelerate student success through intuitive and effective learning tools and content that maximize a teacher’s time and a student’s learning experience. We do all of this in a supportive, collaborative environment where you can grow your career in a way that fits into your life. How can you make an impact? As a Manager, Supply Chain Data Analytics, you will lead and develop the Supply Chain Data Analytics team and play a critical role in shaping how data, analytics, and automation are used across McGraw Hill’s integrated Global Supply Chain organization. This role is responsible for building and executing a supply chain analytics strategy that drives decision-making, operational excellence, and business outcomes across Forecasting, Inventory Planning, Sourcing, Logistics, and broader Supply Chain functions. The Manager, Supply Chain Data Analytics provides hands‑on guidance and technical leadership while enabling their team to deliver scalable, high‑impact analytics. This role offers the opportunity to define and scale analytics capabilities that will shape how McGraw Hill’s supply chain operates for years to come. This is a remote position open to applicants authorized to work for any employer within the United States. While this position is remote, preference will be given to candidates based in the Eastern or Central Time Zones.

Requirements

Bachelor’s Degree required, preferably in Data Analytics, Computer Science, Statistics, Mathematics, Information Systems, Engineering, or a related field; Master’s Degree preferred.
7+ years of experience in data analytics, data science, quantitative analysis, or supply chain analytics, with demonstrated progression in scope and responsibility.
3+ years of experience leading, mentoring, or managing analytics professionals in a business environment.
Strong analytical and technical background, with hands-on experience using SQL, Python (and/or R), Alteryx, and data modeling techniques.
Demonstrated experience with data visualization and business intelligence tools such as Tableau and/or Power BI.
Proven ability to design and scale automated analytics solutions using Power Automate, PowerApps, and AI-enabled tools.
Familiarity with modern data architectures (e.g., data warehouses, lakes, lakehouses, cloud analytics platforms) and partnering with IT on analytics solutions.
Experience leading cross-functional analytics initiatives and managing multiple projects with competing priorities.
Strong business acumen with the ability to connect analytical work to operational and financial outcomes.
Excellent communication skills, with the ability to influence stakeholders, present to senior leadership, and translate complex analytics into clear insights.
Ability to balance strategic thinking with hands-on leadership in a fast-paced, matrixed environment.

Responsibilities

Lead, coach, and develop a team of Supply Chain Analysts, providing clear direction, performance feedback, career development, and mentorship.
Set the vision, roadmap, and priorities for supply chain analytics in alignment with business strategy and leadership objectives.
Establish analytics standards, best practices, and governance to ensure consistency, accuracy, scalability, and reuse across reporting, dashboards, and models.
Partner with Technology and Data teams to shape and evolve data platforms, pipelines, and tools so they reliably support current and future supply chain analytics needs, scalability, and performance.
Oversee the design, development, and maintenance of queries, data sets, dashboards, and analytical models used to monitor and manage supply chain performance.
Enable and expand data science, AI, and machine learning use cases that improve forecasting, risk identification, and operational performance
Lead initiatives to automate analytics workflows, data pipelines, and reporting using tools such as SQL, Python, Alteryx, Power Platform, and AI/ML capabilities.
Ensure analytics outputs are effectively communicated through data storytelling tailored to senior leadership and operational audiences.
Prioritize and balance ad-hoc, tactical, and strategic analytics requests to ensure focus on highest-value initiatives.
Champion continuous improvement by identifying opportunities to simplify processes, eliminate manual effort, and improve decision quality through data.