Service Manager, Forecasting and Planning Analytics

McKesson•Richmond, VA

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. We are looking for an experienced professional to fill our Forecasting and Planning Analytics position. The Forecast Planning position is a pivotal role designed to enhance and optimize the supply chain operations, demand planning process, ensuring accurate forecasts within the Medical Surgical CIO department. Reporting directly to the Data and Advanced Analytics Service Category Manager, this role requires an exceptional leader capable of driving supply chain efficiency, forecast accuracy, optimize inventory and enhance service delivery to support business objectives. The ideal candidate will spearhead strategies to optimize inventory management, demand forecasting, and supplier collaboration, leveraging advanced analytics and technology to ensure a seamless, resilient, and customer-focused supply chain. Job Responsibilities: We are seeking a Data Science Lead to design and deliver advanced data-driven solutions for supply chain operations. This role combines domain expertise in supply chain management with data science and analytics skills to build predictive models and data products that optimize forecasting, demand planning, and operational efficiency.

Requirements

Degree or equivalent experience.
Typically requires 12+ years of professional experience and 4+ years of management experience.
Strong knowledge of supply chain strategy, forecasting, demand planning, inventory optimization, cost management and customer satisfaction.
Strong Experience in data science and with years of experience in analytics.
Experience with forecasting models (ARIMA, SARIMA, XGBoost) and libraries (Prophet, StatsForecast, Darts).
Hands on Experience with Databricks
Experience in designing time-series forecasting models for supply chain use cases.
Hands-on experience with machine learning and statistical modeling.
Strong communication and collaboration skills to work across business and technology teams.
Proven ability to build teams, lead projects, and manage stakeholder engagement.
Candidate must be authorized to work in the U.S, now or in the future, without the support from McKesson.

Nice To Haves

Familiarity with data engineering concepts is a plus.

Responsibilities

Lead strategic supply chain planning to improve efficiency, reduce costs, and enhance service levels.
Apply advanced forecasting models and analytics to optimize inventory and ensure product availability.
Build strong supplier partnerships and implement performance metrics for reliability and quality.
Drive technology integration for ERP and logistics systems to improve visibility and decision-making.
Champion continuous improvement using lean methodologies to reduce waste and boost agility.
Collaborate cross-functionally with sales, finance, IT, and operations to align supply chain strategies with business goals.
Manage risk and resilience by identifying potential disruptions and implementing mitigation strategies.
Deliver actionable insights through accurate reporting on forecasts, inventory, and service performance.
Analyze variances between actual performance and forecasts, recommending improvements.
Lead and mentor a team , fostering collaboration, innovation, and alignment with McKesson’s ICARE and ILEAD values.
Demand planning: Predicts future customer requirements to keep products available while avoiding overstock, which helps reduce unnecessary costs and storage needs.
Inventory optimization: Control stock levels to balance the expense of holding extra inventory with the risk of running out and missing sales.
Production and logistics scheduling: Apply forecasts to organize production timelines, allocate resources effectively, and improve logistics, helping to avoid bottlenecks.
Cost management: Finds ways to lower costs by reducing last-minute orders, limiting excess stock, and preparing for possible price changes.
Customer satisfaction: Improve customer loyalty and satisfaction by ensuring products are delivered on time by accurately predicting demand spikes and seasonal fluctuations.