Job description

UP’s Advanced Analytics team is looking for a data scientist who is passionate about turning data insights into action. The team is responsible for using machine learning, predictive analytics, text mining, forecasting techniques, operations research, and statistical analysis to solve problems for the enterprise. Ideal candidates will have knowledge and experience with applied mathematical/statistical modeling. Candidates should be able to identify and apply mathematical optimization techniques for efficient resource utilization or be able to use advanced statistical modeling for building competitive intelligence programs.

Accountabilities

  • Uncover, learn, and understand business problems, processes, and their characteristics.
  • Create machine learning solutions for various business problems.
  • Design, develop and implement mathematical modeling and optimization algorithms to deliver improvements in business processes.
  • Design, develop and implement predictive and descriptive data mining models to support data driven decision making.
  • Interpret and analyze results of predictive/data mining models.
  • Analyze, explain, communicate and document model results with expanded project team.
  • Follow through to ensure models meet stakeholder’s needs and are incorporated into existing systems or workflows.

Qualifications

Required
  • A Bachelor's degree or commensurate experience in this field
  • Advanced problem solving skills
  • Customer-focused AND goal-oriented
  • Experience with Scripting and coding languages such as: Bash, Perl, Python, Go or Java
  • Knowledge and experience with RHEL / CentOS
  • Analytical and detail oriented
  • 4 or more years of work experience
Preferred
  • Experience with Python, R, MatLab, SAS, SPSS or equivalent statistical software package/language
  • Experience solving analytical problems using statistical/mathematical modeling/methods
  • Experience with applied statistics, machine learning, and predictive model development against diverse data sets
  • Experience with any Operations Research software package (e.g., GUROBI, CPLEX, XpressMP, GAMS, SimProcess)
  • Knowledge in one or more of the following techniques: Linear Regression, Logistical Regression, CARTS, Random Forest, Queuing Theory, Neural Networks, Deep Learning, Clustering

Physical Requirements

  • While performing the responsibilities of the job, the employee will spend extended hours in front of a computer screen

Work Conditions

  • 18 years of age or older

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