Predictive Modeler

  • 36520
  • Non-Life - Data Science
  • |
  • Michigan, United States
  • |
  • Jan 2, 2020
Insurance
RESPONSIBILITIES
  • Under supervision use technical and qualitative experience to design, build, test, validate and implement moderate to complex pricing, operational and financial predictive models to drive profitable growth, fight fraud and make sound business decisions.
  • Work on intermediate-level assignments that require a firm understanding of business requirements.
  • Conduct requisite analyses, using a variety of statistical analysis techniques including data mining, research and analysis. Research and incorporate relevant external data sources into the analysis process.
  • Understand and analyze complex insurance, banking and/or other risk factors using mathematical and computational concepts to create models.
  • Provide technical and quantitative support to formulate, test, interpret, validate and maintain mathematical ratemaking or capital models.
  • Create visualizations and dashboards of cause and effect relationships and big data sets into user-friendly, easy to understand presentations.
  • Transform raw data into actionable business solutions.
  • Improve decision making by providing relevant data-driven analysis and presenting results and detailed recommendations to internal department management and business line leadership/contacts.
  • Take on a new perspective to existing solutions to resolve complex problems.
  • May lead projects or projects steps within a broader project or have accountability for ongoing activities or objectives.
  • May serve as a resource to les experienced modelers working on research projects.
  • Create and maintain detailed documentation of analytics projects.
  • Provide management and staff with instructions on modeling techniques to ensure an understanding of methodologies used to develop recommendations and reports.
  • Assist management and departmental team in improving methods, analysis and data gathering techniques.
  • Develop programs and procedures for users outside of the team.
  • Demonstrate in-depth knowledge of own discipline.
  • Maintain up-to-date knowledge of industry research, developments, changing trends and jurisdictional issues.
QUALIFICATIONS
  • Bachelor’s degree in Mathematics, Actuarial Science, Statistics or a related field.
  • Three years of statistical/predictive modeling or related experience.
  • One-year experience in exploratory data analysis.
  • One-year experience conducting statistical analysis, business analytics and/or related working with very large data, and building predictive modeling.
  • Using tools and techniques for statistical analysis programming and database querying in support of advanced analytics.
  • Utilizing desktop computing skills, including use of one or more word-processing, spreadsheet and presentation graphics software programs.
  • Manipulating data in preparation for modeling exercise.
  • Producing and compiling reports.
  • Formulating and interpreting mathematical models.
  • Analysis of technical studies and data and draw sound conclusions.
  • Knowledge of predictive modeling techniques and principles.
  • Advanced knowledge of SAS, SQL, Python, R or similar data mining application.
  • Solid understanding of programming, database and data mining principles.
  • Ability to research and utilize new programming and modeling techniques.
  • Ability to apply new statistical procedures.
  • Demonstrate strong analytical and problem solving skills.
  • Create advanced programs from ground up.
  • Teach analysts within and outside of the team to utilize new advanced analytics techniques.
  • Make oral presentations to business units
  • Represent the department on inter-department teams.
  • Communicate effectively with others in a work environment both orally and in writing.
  • Preferred:
  • Master’s degree in Mathematics, Actuarial Science, Statistics or a related field
  • Working in a Personal Lines Property and Casualty with specific focus on actuarial research.
  • Predictive modeling in insurance environment.
  • Documenting and presenting results of modeling projects to senior management.
  • Completing actuarial research relating to insurance operations.