Stellantis is hiring a Forecasting Analyst to ensure optimal service parts availability across our North American network. In this role, you will leverage forecasting tools and data analysis to create accurate, actionable demand plans that support service level improvement, inventory optimization, and supply chain stability.

What You’ll Do

Develop, maintain, and refine service parts demand forecasts using the F2K legacy system and MARCS demand planning tools.
Analyze historical trends, seasonality, product life cycle, and service rate performance to improve forecast accuracy.
Maintain safety stock calculations and recommend adjustments to balance part availability with inventory cost.
Perform depot-level UCS analysis to identify opportunities for inventory and customer service improvements.
Partner with Inventory Planning to align forecast outputs with stocking strategies.
Work with suppliers and purchasing teams to communicate demand changes, risks, and capacity constraints.
Collaborate with field operations, network design, and depot operations teams to align strategies.
Execute long-term inventory health plans aligned with S&OP and Mopar strategic priorities.
Analyze inventory availability, fill rates, and service performance to identify improvement opportunities.
Perform safety stock analysis and recommend adjustments based on demand variability, lead-time changes, and risk mitigation needs.
Support depot-level UCS analysis to ensure stocking policies optimize space utilization and service coverage.
Lead digital transformation efforts to modernize reporting pipelines using Power BI, SQL, and advanced analytics tools.

What We’re Looking For

Proven experience in demand forecasting, inventory planning, or supply chain analytics.
Proficiency with forecasting tools, data analysis, and statistical modeling.
Strong analytical skills with the ability to interpret historical data and trends.
Excellent collaboration and communication skills to partner with cross-functional teams.
Ability to manage multiple priorities and drive process improvements.