SIOP Analyst

ESI•Piscataway, CT

About The Position

The SIOP Data Analyst supports the Sales, Inventory, and Operations Planning (SIOP) process through reporting, data analysis, and master data management. This role is responsible for maintaining data accuracy, supporting business reporting, and contributing to data readiness initiatives. The ideal candidate is analytical, detail-oriented, and able to collaborate effectively across Supply Chain, Operations, Sales, and Finance.

Requirements

Bachelor’s degree in supply chain, Business Analytics, Data Analytics, Mathematics, Statistics, Business Administration, or a related field.
0–3 years of experience in analytics, planning, supply chain, or related business functions.
Advanced Microsoft Excel skills, including Pivot Tables, Power Query, lookup functions, and data visualization.
Strong analytical, problem-solving, and organizational skills.
Ability to work with large datasets and ensure data accuracy.
Effective communication and collaboration skills.

Nice To Haves

Experience with JDE, SAP, SAP IBP, or other planning systems is preferred
Basic SQL knowledge is preferred
Experience with Power BI, Tableau, or similar reporting tools is preferred
Exposure to Supply Chain Planning, Demand Planning, Inventory Management, or SIOP/S&OP processes is preferred
Experience supporting master data management or data governance activities is preferred.

Responsibilities

Collect, validate, and maintain data from ERP, planning, and business systems.
Develop and maintain SIOP reports, dashboards, and performance metrics.
Track and report key KPIs, including: Forecast Accuracy, Forecast Bias, Days Inventory Outstanding (DII), On-Time Delivery (OTD), Schedule Compliance.
Planning Master Data Completeness (%)
Analyze trends and provide insights to support planning and operational decision-making.
Maintain and validate planning master data within ERP and planning systems.
Support master data governance to ensure consistency and compliance with established standards.
Identify and resolve data quality issues impacting planning processes.
Support data cleansing, standardization, and data readiness activities.
Assist with system testing, validation, and reporting for planning system enhancements.