Predictive Modeler / Consultant

  • 33112
  • Non-Life - Actuarial
  • |
  • Ohio, United States
  • |
  • Nov 21, 2017
  • Consults with business customers to identify scope and specifications for largest most complex project requests and may initiate research/investigation of observed needs. Researches competitive industry trends, methodologies, and data sources to complete the project. Incorporates established best practices into research projects and final product.
  • Creates project plans based on customer input, data availability and best practices. May require planning and integration of work conducted by others. Establishes criteria, assumptions, data sets and parameters for robust and fully encapsulated analysis. Negotiates timelines, priority and format of final deliverables.
  • Performs analysis of complex multivariate data and business scenarios based on experience and established department methodologies. Provides portfolio and trends analysis, vintage analysis, comparative analysis of markets/territories, actuarial judgment/ quantitative risk management judgment, and any additional assessment as indicated by project plan or ongoing identification of issues. Evaluates deliverables for accuracy, quality and relevance based on statistical and actuarial expertise.
  • Prepares written reports of findings for discussion and or presentation to business partner and department leadership. Interprets findings, provides options for consideration and recommendations for resolution of original issue/request.
  • Provides guidance, information and support for regulatory review of work product. Provides ongoing consulting for Pricing and/or Product use of work product.
  • Provides assistance for measuring the rate / profitability impact of work product.
  • Designs and develops standard reporting packages and monitors results of product performance. Validates and updates models periodically and provides validation reports.
  • Contributes expert/actuarial opinion on the structure of analysis, interpretation of findings, and usefulness of results. Responsible for the development and maintenance of models and best practices to provide the functionality necessary to drive business objectives.
  • May lead core studies or portions of the studies that require extended timelines, extensive data collection, leveraging associate knowledge, identifying root cause and associated influence. Initiates or leverages competitive research findings.
  • Reviews, validates and quality checks the work of others. Provides guidance to other associates.
  • Performs other related duties as assigned.
  • Undergraduate studies in mathematics, actuarial analysis, marketing research or related fields. Postgraduate degree strongly preferred.
  • Strong preference for in-depth knowledge and working experience with Generalized Linear Models (GLM) and Machine Learning.
  • A minimum of 3 years' experience with large data bases (at least 5 years' for Consultant level).
  • Experience in leading a statistical/actuarial based analytical project.
  • Experience with statistical modeling software (Emblem, SAS, R, etc).
  • Minimum of six years related experience with large data bases, analytical problem solving in a business environment, and with programming models and queries.
  • Experience with SAS, SQL and other statistical software building models and manipulation of data.
  • Experience working with insurance data other comparable industry data experience to identify trends and opportunities.
  • Experience in conceptualizing and designing models to address business needs. Experience in leading a statistical/actuarial based analytical project.
  • Detailed knowledge of data management, project management and complex data/actuarial analysis. Prefer some industry knowledge.
  • Excellent verbal and written communication skills for interaction with business unit leadership and team members.
  • Proven excellence in problem solving, analytical, research and quantitative analysis skills, and analytical working techniques including: regression, decision trees, multivariate analysis, etc. Proficiency in developing ad hoc queries using SQL and SAS.