Statistician

Posted Date 2 months ago(1/23/2020 11:50 AM)
City
Irving
State/Province
Texas

Overview:

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Celanese is a Fortune 500 global chemical innovation company that engineers and manufactures chemicals used in products essential to everyday living. Headquartered in Dallas, TX, we employ over 7,700 dedicated people working between 43 facilities across 18 countries. We are committed to employee growth and creating shareholder value to ensure continued opportunities make a difference. Our company focuses on the safety of its employees, provides competitive compensation (including benefits starting day 1), and emphasizes giving back to the community. For more information about Celanese and our products please visit www.celanese.com

 

 

A Data Scientist at Celanese will report to a Global S&OP Director and will work with multiple global and regional S&OP professionals, including demand and supply planners, schedulers, and inventory specialists, supporting all Celanese product lines.  This person will conduct in-depth mathematical analysis, look for actionable insights, and use this information to develop data-driven solutions in support of global S&OP processes.  

Responsibilities:

  • Build and maintain monthly time series sales forecasts, coordinate with S&OP team members to implement into demand planning process.
  • Create and manage process to continually monitor the performance and accuracy of forecast models.
  • Conduct various data science experiments to support and help automate certain processes within the global S&OP organization.
  • Effectively communicate results of complex mathematical models to a variety of stakeholders, using data to help persuade business outcomes.
  • Identify opportunities for cost savings and process improvement across the supply chain

 

 

Required Knowledge/Skills/Abilities:

  • Highly proficient in R and/or Python languages (modeling tools) 
  • Expert in time series statistical modeling, with strong experience in commonly used forecasting models such as ARIMA, Holt Winters, etc.
  • Demonstrated experience in machine learning, in models such as neural nets.
  • Ability to apply advanced mathematical models, (i.e. regression, clustering) to common business scenarios.
  • Self-starter who can work independently and manage time effectively.
  • Familiarity with S&OP processes and associated tools a plus.

Qualifications:

  • B.S. in Data Science, Computer Science, Statistics, or a related quantitative field. M.S.  preferred
  • 5+ years of relevant experience

Application Methods:

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