Data Scientist

Inventory Data Engineering & Analytics (IDEA) Data Engineer

The position bridges data engineering, advanced analytics, and business partnership to enable high-impact inventory decisions.

Key Responsibilities

Design, build, and maintain scalable inventory data pipelines and curated datasets supporting forecasting, planning, and execution.

• Partner with senior IDEA leaders to translate inventory and supply chain problems into analytical and data engineering solutions.
• Develop and productionize analytical models (forecasting, segmentation, root-cause analysis) used by planning and operations teams.
• Ensure data quality, reliability, and observability across inventory datasets and reporting layers.
• Contribute to architectural decisions for data platforms, tooling, and standards within IDEA.
• Mentor analysts and engineers on best practices in SQL, Python, and analytical problem solving.

• Work closely with stakeholders across Supply Chain, Finance, and Operations to drive data-informed inventory decisions.
• Act as a technical and analytical partner to senior IDEA contributors, supporting roadmap definition and delivery.
• Communicate complex analytical findings clearly to both technical and non-technical audiences.

• Strong experience in data engineering and analytics roles, preferably in inventory or supply chain domains.
• Advanced SQL and Python skills; experience with distributed data processing frameworks is preferred.
• Proven ability to move from ambiguous business questions to well-structured data solutions.
• Experience building dashboards, metrics, and analytical assets used by business teams.
• Strong ownership mindset with the ability to operate independently while collaborating closely with senior leaders.

• Experience supporting forecasting, replenishment, or inventory optimization use cases.
• Familiarity with modern data stack tools and cloud-based data platforms.
• Demonstrated impact through delivery of end-to-end data or analytics products.