Data Scientist

  • 32501
  • Life - Other
  • |
  • Missouri, United States
  • |
  • Mar 15, 2017
Reinsurance Organization
RESPONSIBILITIES
  • Modeling: Develop and enhance statistical models for the applications in insurance industry, including mortality, morbidity, persistency, fraud, consumer response, etc. for use internally or externally.
  • Provide internal and external clients with an expert review on vendor and/or client-generated models.
  • Commercial Applications: Understand client’s objectives and support the development of commercial applications of predictive models for use in underwriting, claims, risk management and/or projections.
  • Data Understanding: When presented with specialist datasets, carry out the full spectrum of data analysis, from the development of statistical analysis plans and design of the database schema, through data cleansing and into the creation of new insights and knowledge based on thorough and deep statistical analysis of the data;
  • Subject Matter Expertise / Client Contact: Provide subject matter expertise in the insurance application of predictive modeling and advanced data analytics. Expand knowledge of insurance products, markets, processes and challenges.
  • Collaboration / Communication: Collaborate with and provide technical support to local offices for predictive modeling and other ongoing projects. Develop strong verbal and oral communication skills whenever possible.
  • Actively participate in other research-related initiatives.
  • Maintain regular and predictable attendance.
QUALIFICATIONS
  • Bachelor’s degree in Math, Statistics, Actuarial Science, Finance, Economics, Bioinformatics or related field.
  • Master’s degree or PhD in Statistics, Actuarial Science, Business, Finance, Economics, Bioinformatics or related field. Preferred.
  • 4+ years of actuarial experience or 2+ years developing statistical models for insurance, health or related applications.
  • 3+ years of experience with statistical modeling for insurance or health related applications (GLM, Decision Trees, Time Series, Regression, and Random Forest etc.). Preferred.
  • Advanced PC and technical skills, including statistical programs (ex.: R, SAS, MATLAB, or Python), spreadsheets and database applications (Access, Oracle, SQL or equivalent technology).
  • Advanced knowledge in statistics and math.
  • Investigative, analytical and problem solving skills.
  • Ability to quickly adapt to new methods, work under tight deadlines and stressful conditions.
  • Ability to work well within a team environment, participate in department/team projects and balance detail with departmental objectives.
  • Strong oral and written communication skills, demonstrating the ability to convey business terminology that is meaningful and well received.
  • Strong ability to handle multiple projects simultaneously.
  • Ability to resolve conflict and foster teamwork.
  • Ability to liaise with individuals across a wide variety of operational, functional and technical disciplines.
  • Ability to translate business needs and problems into viable/accepted solutions.
  • Knowledge of actuarial concepts including mortality, morbidity, and persistency studies.
  • Knowledge of life, health, and/or annuity products.
  • Knowledge of life insurance underwriting.
  • Solid experience with R, SAS, MATLAB or Python.
  • Knowledge of SQL and VBA.
  • Knowledge of insurance risk analysis.
  • Experience in computational finance and econometrics.
  • Willingness to travel domestically and internationally.