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Data Scientist II in Lansing, MI at AF Group

Date Posted: 11/18/2018

Job Snapshot

Job Description


The main focus for this role is developing/monitoring models used in multivariate analysis, linear modeling and data mining. This would include developing and testing predictive risk models; interact, understand and articulate the complex mathematical and computational learning concepts (to appropriate staff).In addition, this position will be expected to understand the business goals (growth) and capital strength and make strategic recommendations to enhance business processes and reflect our strategic goals.


  • Responsibilities will be multi-disciplinary and will include:
    • Provides technical and quantitative analysis for predictive modeling group.
    • Assists in statistical data mining and actuarial research by applying advanced statistical concepts.
    • Uses computer technology, computer modeling, spreadsheet applications, software tools, and programming languages.
    • Participates in and is responsible for projects requiring advanced statistical analyses, innovative research, mathematical calculations, and technical skills.
    • Conducts research utilizing predictive modeling.
    • Interprets data and identifies correlations using both univariate and multivariate analysis.
    • Participates in and is responsible for advanced projects.
    • Presents findings and recommendations to appropriate groups.
    • Prepares and delivers summary reports to the relevant or affected areas within the company. Helps to determine what actionable steps can be taken based on the findings.
    • Communicates and trains users on model results.
    • Develops custom, explainable models that enhance business processes to reflect corporate goals, experience, and current market conditions using pattern recognition, evolutionary computation, and machine learning algorithms.
  • Document model requirements.
  • Examine and analyze data to determine optimal modeling approach.
  • Identify candidate risk factors.
  • Build models using training, test, and cross-validation data sets.
  • Share model results.
  • Finalize model.
  • Delivers conclusions.
  • Deploy and maintain models with or without the assistance of the IT department


  • Further involvement in the implementation of predictive model results into the appropriate system.
  • Additional communication to all affected departments. This includes the creation of appropriate documents (PowerPoint presentations, etc.) to be used in the communication of predictive model results to the company.
  • Lead the deployment and maintenance of models with or without the assistance of the IT department.


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