Remote Advisory Engineer: Process Optimization & Data Tools

Ricoh Americas Corp.

United States

Hybrid

USD 90,000 - 120,000

Full time

14 days+

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Job summary

Ricoh USA, Inc. is seeking an Advisory Engineer to drive process optimization across its Rialto, CA distribution and regional fulfillment center network.

You will plan and execute engineering projects to deliver measurable improvements and financial benefits throughout the supply chain. Candidates should hold a Bachelor's degree in Industrial Engineering or related field and have 12 months' experience with data analysis tools such as Excel VBA, Python, SQL, PowerBI, and related modeling

Qualifications

  • Bachelor's degree in Industrial Engineering or related field is required.
  • 12 months' experience in the job offered or related occupation with data analysis tools.
  • Experience with Excel VBA, Python, SQL, PowerBI and data analysis frameworks is required.

Responsibilities

  • Deliver transformational and quantifiable improvements and financial benefits across the supply chain.
  • Plan and execute process-engineered projects within Ricoh's distribution and fulfillment network.
  • Require commuting distance to Rialto, CA; remote work from home permitted.

Education

Bachelor's degree in Industrial Engineering or related field

Tools

Microsoft Excel VBA
SketchUp CAD
Python
SQL
Data Envelopment Analysis
Predictive Modeling
Financial Modeling
PowerBI
Snowflake
Pandas
NumPy
Matplotlib
Scikit-Learn
Kinaxis Rapid Response
Descartes
OBIEE
Oracle eBiz Suite
Asana

Job description

Ricoh USA, Inc. is seeking an Advisory Engineer to drive process optimization across its Rialto, CA distribution and regional fulfillment center network.

You will plan and execute engineering projects to deliver measurable improvements and financial benefits throughout the supply chain. Candidates should hold a Bachelor's degree in Industrial Engineering or related field and have 12 months' experience with data analysis tools such as Excel VBA, Python, SQL, PowerBI, and related modeling

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