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Data Science Actuary, Americas Data Solutions

Remote: 
Full Remote
Contract: 
Salary: 
132 - 202K yearly
Experience: 
Senior (5-10 years)
Work from: 
Maryland (USA), United States

Offer summary

Qualifications:

Bachelor's degree in Math or related field, FSA accreditation or equivalent, 7+ years of actuarial experience, 3+ years statistical modeling experience, Advanced predictive modeling skills.

Key responsabilities:

  • Provide actuarial expertise for data solutions
  • Lead and design models focusing on risk
  • Evaluate new external data sources
  • Enhance advanced analytics capabilities
  • Educate teams on modeling tools and techniques
Reinsurance Group of America, Incorporated logo
Reinsurance Group of America, Incorporated Insurance Large https://www.rgare.com/
1001 - 5000 Employees
See more Reinsurance Group of America, Incorporated offers

Job description

You desire impactful work.

You’re RGA ready

RGA is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. A Fortune 500 Company and listed among its World’s Most Admired Companies, we’re the only global reinsurance company to focus primarily on life- and health-related solutions. Join our multinational team of intelligent, motivated, and collaborative people, and help us make financial protection accessible to all.

Position Overview

The Data Science Actuary, Americas Data Solutions is a qualified actuary with data science capabilities; someone who combines curiosity, technical skills, and collaboration to create innovative data-solutions; and a leader on project-teams consisting of data scientists, actuaries, underwriting, IT, and business developers. The Data Science Actuary will work on data product innovation for internal and industry initiatives that unlock benefits of new & existing data-sources & data-solutions through exploratory analysis, novel insights, model maintenance, and model R&D.

We are open to remote candidates in the US and Canada.

Responsibilities

  • Provide actuarial and analytical expertise to support the development or enhancements of commercial data-solutions at RGA.
  • Lead, design, create and interpret end-to-end model’s with a typical focus on risk scores.
  • Evaluate new external data sources and explore new applications of non-traditional data sources for RGA and our clients.
  • Enhance RGA’s advanced analytics capabilities through the innovative application of cutting-edge techniques to generate novel business insights.
  • Leverage newly developed solutions and advanced analytics capabilities across different business units
  • Offer robust risk management skills and held accountable to any data processing or modeling exercise:
    • Understanding business context & where material scope for error lies
    • Adhering to professional standards, best practices, and ethical guidelines
    • Understanding the strengths and limitations of a modeling approach
  • Educate and/or lead others on tools / techniques their actuarial peers will not have had a formal education in
    • Applications, risks, transparency, quality assurance & peer review, ethical guidelines
    • Staying abreast of new techniques, but focusing on practical applications
    • Liaising with RGA's Global D&A team for more sophisticated data science applications
    • Contributing to RGA's global analytics community, routinely sharing, maintaining consistency of approach
Requirements

  • Bachelor's degree in Math, Finance, Statistics, Actuarial Science, Computer Science or related field
  • FSA accreditation or equivalent
  • 7+ years of actuarial experience in life insurance/reinsurance
  • 3+ years statistical on-the-job modeling experience (not exam based) for insurance or related applications (Regression, Decision Trees, Time Series, etc.)
  • Statistical programs/languages (R or Python)
  • Advanced spreadsheet skills (Excel/VBA) and database applications (SQL, Snowflake, Oracle,...)
  • Advanced predictive modeling skills
    • Tree-based models + GLMs
    • Cross-Validation, Residuals and model diagnostics
    • Basic Statistical concepts for feature engineering (e.g. percentiles, standardization, correlations, risk ratios / chi-square test, splines, and other non-linear transformations)
    • Pro-active use of insurance expertise & actuarial concepts to feature engineering and model evaluation
  • Basic machine learning models/concepts (Clustering, Random Forests, GBM/XGBoost & other boosting algorithms)
  • Advanced exploratory data analysis skills - Plots and graphics (BI/ggplot)
  • Strong curiosity and a self-motivated desire to learn new skills and techniques and apply those to traditional life insurance problems
  • Ability to compile, analyze, refine, model and interpret very large data sets
  • Ability to incorporate expert judgment into statistical modeling techniques
  • Transform data to enhance its predictive value (feature engineering)
  • Guide stakeholders through evaluations of third-party data and predictive models
  • Highly advanced oral and written communication skills, sharing insights and explaining technical topics
  • Advanced documentation skills consistent with Actuarial Standards of Practice (ASOPs)
  • Advanced ability to manage multiple projects and/or teams simultaneously
  • Advanced ability to liaise with a wide variety of operational, functional, and technical disciplines
  • Strong collaboration skills to work well within a team environment
  • Highly advanced ability to translate business needs and problems into viable/accepted solutions
  • Highly advanced investigative, analytical and problem-solving skills
Preferred

  • Experience with product design / pricing / experience studies
  • Reinsurance industry experience
  • Master’s degree or PhD in Statistics, Actuarial Science, Economics, or related field
  • 6+ years of experience with statistical modeling for insurance
  • 2+ years of project lead, supervisory or management experience
  • Ability to create and maintain commercial data-solutions
  • Familiar with actuarial modeling platforms (AXIS, Prophet, Exp Studies etc.)
  • Basic data engineering capabilities (Python, Scala)
  • Advanced machine learning models/concepts (SVM’s, GAN’s, Neural Networks/Deep Learning, Naive Bayes, NLP)
  • Advanced statistical concepts for feature engineering for dimensionality reduction such as PCA’s, SVD’s, and clustering
  • Advanced experience in computational finance, econometrics, statistics and math
  • Strong persuasion and negotiation skills when working with internal/external customers
  • Strong people management skills, demonstrating the ability to lead, mentor, and develop associates; including the ability to delegate key areas of responsibility
  • Expert knowledge of life, health, and/or annuity products

What You Can Expect From RGA

  • Gain valuable knowledge from and experience with diverse, caring colleagues around the world.
  • Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought.
  • Join the bright and creative minds of RGA, and experience vast, endless career potential.

Compensation Range

$132,430.00 - $202,455.00 Annual

Base pay varies depending on job-related knowledge, skills, experience and market location. In addition, RGA provides an annual bonus plan that includes all roles and some positions are eligible for participation in our long-term equity incentive plan. RGA also maintains a full range of health, retirement, and other employee benefits.

RGA is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, age, gender identity or expression, sex, disability, veteran status, religion, national origin, or any other characteristic protected by applicable equal employment opportunity laws.

Required profile

Experience

Level of experience: Senior (5-10 years)
Industry :
Insurance
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Spreadsheets
  • Analytical Thinking
  • Social Skills
  • Verbal Communication Skills
  • Problem Solving
  • Organizational Skills
  • Curiosity
  • People Management

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