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Data Scientist - Modeling & Forecasting

Employment Type: Full Time

Work Hours: 40 hours+ per week

Education Requirements

College degree or higher in a mathematics-oriented discipline; or equivalent related experience.

Experience Requirements

• College degree or higher in a mathematics-oriented discipline; or equivalent related experience.

• Previous experience (including academic) in analytics, statistics, modeling, and/or decision science.

• Strong background in programming; experience with SQL and SAS preferred but not required.

• Technical understanding of databases, querying, and large data structures.

• Proficiency with Microsoft Office tools; strong Excel skills preferred.

• Familiarity with basic accounting concepts and business considerations.

• Ability to quickly assimilate new business concepts, technical skills and software/programming languages.

• Strong analytical, interrogative, and problem-solving skills.

• Effective communication skills and the ability to be influential through both written and verbal interactions with a variety of audiences.

• Flexibility to work independently and collaboratively as a member of a team.

• Aptitude for maintaining productivity while multi-tasking in a fast-paced environment.

Responsibilities

  • Build new predictive models of a variety of key outcomes and verify model performance.
  • Develop and enhance advanced modeling techniques for predictive analytics.
  • Extract and analyze data from both internal and external data sources.
  • Refresh existing models with additional data and/or new techniques or variables.
  • Document and annotate model development, improvement, and performance.
  • Communicate model development and improvement to both technical and non-technical audiences.
  • Implement models into usable SAS code and Excel templates for use by other analysts.
  • Evaluate portfolio purchase opportunities and produce pricing recommendations.
  • Review performance of existing purchases and produce updated forecasts.
  • Provide insight and observations for improvements in operations and pricing.

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