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Senior Actuarial Analyst - Data Science

Job ID: 1007657
Date Posted: May 23, 2022
Department ID: TS0504 Actuarial - Pricing - Other th
Company: TMNA Services LLC

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Job Description

Marketing Statement

Tokio Marine North America Services (TMNAS) provides professional support services to Tokio Marine Group companies in the United States, including Tokio Marine America, First Insurance Company of Hawaii, and Philadelphia Insurance Companies. Customer service is our focus and our passion! TMNAS adds value in all that we do, providing the best professional service to our business partners, allowing them to achieve their goals. Our talented team delivers actuarial, audit, corporate communications, financial and investment, human capital services, information technology, legal, and payroll expertise to our customers.

Duties

JOB SUMMARY / Opportunity to Work Remote                                                                                                                                                  

The TMNAS Actuarial Pricing Section works with internal and external customers to handle pricing needs for sister companies with market share over $3B countrywide. The pricing services include data development, a reporting platform for self-service pricing reports, exposure management, predictive analytics, rate maintenance, large account pricing, and product development.

The Sr. Actuarial Analyst/Actuarial Data Scientist needs to be able to work with internal and external customers to provide the information supporting business decisions. The position requires ability to learn data definitions and structures related to insurance operations and the ability to support a self-service reporting platform for clients.  Knowledge of predictive analytics is also required as the company is establishing its predictive analytics services.

                                                                                                                                                                                                               

JOB RESPONSIBILITIES                                                                                                    

  • Gather and organize internal and external data into structures that can be used to support the reporting needs of the client sister companies
  • Use or create SQL sourced data extracts from source data systems
  • Provide support for Predictive Model development including work with external vendors, development of predictive models using Akur8 software, validation of models, implementation of models, and maintenance of existing models
  • Work within a collaborative team environment
  • Design, develop, enhance, produce and interpret key property and casualty insurance reports for both internal and external distribution
  • Comply with proper internal controls as necessary to conduct job functions and carry out responsibilities and/or administrative activities
  • Successful completion of CAS actuarial exams or the CAS Institute’s Certified Specialist in Predictive Analytics exams within the guidelines set in the TMNAS Actuarial Student Program
  • Understanding of quantitative tools, techniques, and statistical methods
  • Basic knowledge of approaches, tools, and techniques for recognizing, anticipating, and resolving actuarial, operational, or process problems

Qualifications

   QUALIFICATIONS 

  • Bachelor's degree with a concentration in actuarial science, math, finance, economics, computer science, or information science & technology
  • 4+ years of property and casualty experience
  • Strong knowledge of SQL required
  • Strong knowledge of Microsoft Office, particularly with Microsoft Excel
  • Experience with other programming languages (e.g. R or Python) or experience with predictive modeling tools is required
  • Prior experience with building, validating, and implementing predictive models required

EEO Statement

Tokio Marine Management is an Equal Opportunity Employer. In order to remain competitive we must attract, develop, motivate, and retain the most qualified employees regardless of age, color, race, religion, gender, disability, national or ethnic origin, family circumstances, life experiences, marital status, military status, or sexual orientation.

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