Monster Energy
Inventory Control Specialist - 2nd Shift
USA - Lakeland, FL
Sponsorship not specified$20k-$26kDetected 21 hours ago
Data AnalysisStatisticsAccountingExcelSAPLogisticsInventory ManagementCollaboration
About the role
- About Monster Energy: Forget about blending in.
- We're the risk takers, the trailblazers, the gamechangers.
- We're not perfect and we don't pretend to be.
Responsibilities
- Our drive is just like our athletes, unrivaled.
- In the position of Spec, Inventory Control you will be Responsible for daily maintenance and accuracy of data contained within SAP, perform daily counts to monitor and maintain inventory levels.
Requirements
- Prefer a Bachelor's Degree in the field of Logistics, Business Administration, or similar field of study
- Additional Experience Desired: Between 1-3 years of experience in inventory control position
- Process and document returns as required following established procedures
- Between 1-3 years of experience in inventory control position
- This employer is required to notify all applicants of their rights pursuant to federal employment laws.
Nice to have
- Familiar with SAP and EDI programs is a plus
- Additional Knowledge or Skills to be Successful in this role: Familiar with SAP and EDI programs is a plus
Skills
- Excel skills, including:
Compensation
- The estimated hourly pay range for this position is listed below.
Company info
- We are much more than a brand here.
- We are a way of life, a mindset.
Equal opportunity
- Employer/Protected Veterans/Individuals with Disabilities
- This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.
- For further information, please review the Know Your Rights notice from the Department of Labor.
Apply directly at Monster Energy →Create a free account for alerts like thisView Monster Energy immigration profile
This listing is sourced directly from Monster Energy's careers page and normalized into a canonical job model.