Develop and maintain analytical models that support demand forecasting, capacity planning, and inventory optimization.
Analyze sales, production, and supply chain data to identify trends, risks, and opportunities.
Partner with functional leaders to improve forecast accuracy, service levels, and operational efficiency.
Build predictive and prescriptive models using advanced statistical, machine learning, or optimization techniques to support SIOP decision-making.
Perform sensitivity analyses and scenario modeling to support long-term capacity and investment planning.
Develop algorithms and models that provide forward-looking insight into supply-demand balance, lead times, and production throughput.
Serve as a key analytics lead in the ERP/MRP system deployment and post-implementation phases.
Ensure data accuracy, integrity, and consistency across systems through close collaboration with IT, Operations, and Supply Chain teams.
Support design and validation of ERP data structures (e.g., BOMs, routings, inventory hierarchies) for effective reporting and planning.
Develop reporting frameworks and KPIs to leverage ERP data for real-time operational insights.
Drive user adoption by helping build intuitive dashboards and analytical tools that connect business needs with ERP capabilities.
Design and maintain interactive dashboards and reports (Power BI, Tableau, or equivalent) to track KPIs such as forecast accuracy, lead times, inventory turns, and customer fill rates.
Translate complex data into clear insights for executive leadership and cross-functional teams.
Automate recurring data reports and develop robust data pipelines for real-time visibility.
Partner with IT and Operations to ensure data quality, consistency, and standardization across all systems.
Contribute to the development of a best-in-class analytics infrastructure to support the company’s growth and digital transformation.
Identify and drive process improvement opportunities within SIOP and related business processes.
Support strategic initiatives in production planning, material control, and procurement through analytical insights.
Partner with Finance and Operations to model performance scenarios and improve alignment between demand and supply.
Communicate findings effectively to both technical and non-technical audiences.

Requirements

Bachelor’s or Master’s degree in Data science, Statistics, Industrial Engineering
3–7 years of experience in analytics, business intelligence, or data science (manufacturing or supply chain preferred)
Experience supporting or integrating with ERP systems (Epicor, SAP, Oracle, or equivalent)
Strong proficiency in SQL and data analysis tools (Python, R, or similar)
Experience building dashboards and data visualizations (Power BI, Tableau, or equivalent)
Solid understanding of SIOP, MRP, and manufacturing operations processes
Excellent problem-solving skills and business acumen; able to link analytics to operational and financial impact
Strong communication and storytelling skills, with the ability to present data to executive and operational audiences
Analytical and detail-oriented thinker
Curious, self-driven, and proactive in problem-solving
Comfortable working with ambiguity in a fast-growing manufacturing environment
Collaborative mindset with cross-functional communication strength
Passion for data accuracy, process improvement, and continuous learning
Excitement about building systems, data models, and insights that scale with a growing business

Benefits

Competitive pay with performance incentives
100% company-paid medical, dental, and vision
401(k) with company match
3 weeks PTO
10 paid holidays
2 floating holidays

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data analysispredictive modelingprescriptive modelingsensitivity analysisscenario modelingdata pipelinesSQLPythonRdashboard development

Soft Skills

problem-solvingbusiness acumencommunicationstorytellinganalytical thinkingcuriosityproactivitycollaborationattention to detailadaptability