Associate Data Science Actuary
United States, Chesterfield, MO, RGA HQ, United States
Full Time Mid-level / Intermediate USD 95K - 147K
Reinsurance Group of America
At RGA, we specialize in providing life and health-related reinsurance and financial solutions to help our clients effectively manage risk and capital.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 Associate Data Science Actuary, Americas Data Solutions is a qualified actuary with data science capabilities. This role involves combining technical skills and predictive modelling to contribute to innovative data products and collaborates on project-teams consisting of data scientists, actuaries, underwriting, IT, and business developers. The Associate Data Science Actuary will focus on data product innovation for internal and industry initiatives by leveraging new and existing data sources and solutions through exploratory analysis, insights, model maintenance, and model R&D.
Responsibilities
- Provide advanced actuarial and analytical skills 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.
- Participates in the development and enhancement of underlying processes and recommends improvements in data analysis /modeling best practice standards
- Expected to face a variety of stakeholders at various levels of seniority
- Offer risk management skills 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
- Have a strong understanding 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
- 6+ years of actuarial experience in life insurance/reinsurance
- 2+ 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)
- 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
- Advanced exploratory data analysis skills - Plots and graphics (BI/ggplot)
- Ability to compile, analyze, refine, model and interpret very large data sets as well as the ability to incorporate expert judgment into statistical modeling techniques
- Transform data to enhance its predictive value (feature engineering)
- Advanced ability to translate business needs and problems into viable/accepted solutions
- 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
- 4+ years of experience with statistical modeling for insurance
- 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)
- Basic machine learning models/concepts (SVM’s, GAN’s, Neural Networks/Deep Learning, Naive Bayes, NLP), and/or basic statistical concepts for feature engineering for dimensionality reduction such as PCA’s, SVD’s, and clustering
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:
$95,750.00 - $147,250.00 AnnualBase 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.
Tags: Clustering Computer Science Data analysis Deep Learning Economics EDA Engineering Excel Feature engineering Finance Machine Learning Mathematics ML models NLP Oracle PhD Predictive modeling Python R R&D Scala Snowflake SQL Statistical modeling Statistics
Perks/benefits: Career development Equity / stock options Health care Insurance Salary bonus Transparency
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