$75K - $95K/yr
Full-time
Medical, Dental, Vision, Retirement, PTO
Posted 11 days ago
Job description
Manufacturing Data Analyst
Employment Status: Full-Time, Salaried/Exempt
Location: Waukegan, IL
Schedule: Onsite daily Monday through Friday from 8 am – 5 pm CT.
Salary: $75,000 - $95,000
Position OverviewThe Manufacturing Data Analyst will enhance supply chain and manufacturing performance through data-driven insights, SIOP reporting, forecasting support, inventory analysis, ERP data validation, and operational KPI reporting.
Key Responsibilities· Deliver accurate and timely business intelligence to support Supply Chain, SIOP, planning, and manufacturing operations.
· Develop and maintain reports and dashboards related to forecast accuracy, inventory health, supplier performance, production efficiency, and operational KPIs.
· Own SIOP data tracking and provide weekly and monthly updates that highlight gaps, risks, and improvement opportunities.
· Partner with Planning, Commercial, Operations, Purchasing, and Finance teams to align demand forecasts with operational capabilities.
· Maintain and improve databases, data models, and reporting tools that support proactive decision-making.
· Analyze historical data to identify trends, variances, risks, and improvement areas in production planning and material availability.
· Validate ERP data, including routings and BOMs, and act as a gatekeeper for master data changes.
· Support monthly forecasting, scenario planning, benchmarking, and continuous improvement initiatives.
Qualifications & Skills· Bachelor’s degree in Computer Science, Data Analytics, Business Management, or equivalent work experience.
· 5 years of experience in supply chain or manufacturing operations with a focus on data analysis, forecasting, and strategic business operations.
· 2 years of experience directly supporting or managing Sales, Inventory and Operations Planning (SIOP).
· Advanced Excel skills, including VLOOKUPs, Pivot Tables, Power Query, SUMIFs, and related functions.
· Experience with ERP/MRP systems such as Microsoft Navision or similar platforms.
· Experience with Power BI, Tableau, or other visualization tools preferred.
· Experience with forecasting and trend analysis tools or methods, including time series and regression models.
· Strong ability to translate complex data into actionable insights for cross-functional stakeholders.
Physical Requirements· Ability to lift up to 15 pounds at a time.
· Ability to sit for prolonged periods while working at a computer.
· Ability to work in a traditional office setting with normal noise levels.
· Ability to view a computer screen for extended periods and review detailed data.
BenefitsThe company offers a comprehensive benefits package that includes medical, dental, and vision insurance, 401(k), paid maternity leave, paid paternity leave, tuition assistance, disability insurance, paid time off and holidays, and additional wellness and lifestyle benefits.
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.
