Company:
Air Liquide

Address:
2700 Post Oak Boulevard Suite 1800
Houston, TX 77056 USA

Manager, Distribution Methods & Logistics Engineering

Reference Code: ALI-11490


Description:

• Analyze present utilization of resources involving Demand Chain Management, Supply Chain Management, Distribution Operations, and Transportation.
• Plan utilization of facilities, equipment, materials, and personnel to improve efficiency of operations using computer based design and analysis tools such as simulation, spread sheet and database analysis.
• Retain ownership and administration responsibilities for all relevant Distribution Systems to include BDS, OPOD, TENOR, DND or any new systems developed under Methods’ direction.
• Assist Product Supply and Product Management with Supply Chain network design and improvement.
• Implement and utilize optimization software.
• Implement and utilize on-board computers and related software utilized by drivers.
• Recommend methods for improving distribution and supply chain efficiency.
• Use Operations Research skills to model the distribution network to optimize it over the short-term and long-term.


Requirements:

• Adequate Industrial Engineering skills/experience to understand and draw logical inferences on the feasibility of the optimization solutions and make appropriate recommendations.
• Extensive training and knowledge of supply chain software
Strong computer/analytical skills (Microsoft Excel, Access, Word, PowerPoint, Project) required. Knowledge of Oracle systems a plus.
• Knowledge of simulation software application.
• Good working knowledge of DOT policy and Current Good Manufacturing Practices.
• Must be extremely detail oriented with good written and verbal communication skills.
• Travel is necessary up to 50%.
• 5-10 years of experience in Distribution, Supply Chain Logistics or related field.
• Project management experience desirable.
• MBA in addition to a Bachelor's degree (B. A.) in Industrial Engineering, Business or Finance from a four-year college or university with strong course content in quantitative analysis employing computer technology and scientific measures.
• Must include academic experience using linear programming, simulation, or other mathematical modeling techniques to solve optimization problems.