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.
Job Description:
RGA Enterprise Services Company (RGA) seeks a Senior Actuarial Assistant to perform experience analysis, data science support, and research for RGA’s Americas business units. This position will assist in the development of predictive modeling solutions, perform research based on Americas experience data and emerging topics of interest, and drive forward future state analytical capabilities within the Americas. Key responsibilities include the following: evaluate and manipulate internal data, vendor data, and client data for the purpose of predictive modeling, experience analysis, research, and financial analysis; develop, maintain and review data analysis/modeling procedures and systems; participate in the development and enhancement of underlying processes and recommend improvements in data analysis/modeling best practice standards including supporting the expansion of the Americas analytics ecosystem; participate in key unit and ad-hoc department projects as needed; create and/or present research based on the Americas historical data and emerging topics of interest; communicate key findings by creating meaningful and professional reports or presentations; and serve as a liaison with other associates and departments. A qualified applicant must live within reasonable commuting distance of Chesterfield, MO. RGA’s compensation package includes an annual bonus plan. RGA also maintains a full range of health, retirement, and other employee benefits. The compensation range noted below indicates that the base pay varies depending on job-related knowledge, skills, experience, and market location. For this particular position, the offered salary is $105,050.00 and is non-negotiable.
Basic Qualifications:
The position requires at least a bachelor’s degree, or its foreign equivalent, in Math, Finance, Actuarial Sciences, Statistics or related field, and at least two (2) years of experience performing in an actuarial capacity in the life insurance industry. A qualified applicant’s experience must include the following skills: 2 years of experience using actuarial software, concepts, and calculations; 2 years of experience using database applications (Access, Oracle, SQL, and/or TOAD); 2 years of experience compiling, analyzing, refining, and interpreting large amounts of data; 1 year of experience developing statistical and/or machine learning models for insurance, health, or related applications (i.e. GLM, Machine Learning, or Time Series); and 1 year of experience using R, SAS, and/or Python in an actuarial setting. Applicant must have also passed at least 5 of the following actuarial exams: P, FM, IFM, FAM (or FAM-L + FAM-S), ALTAM, ASTAM, SRM, PA, ATPA, or FAM.
Candidates who are interested in this position should select “Apply” below.
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:
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.
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