Assistant Data Science Engineer

Reinsurance Group of America, Incorporated is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. They are seeking an Assistant Data Science Engineer to support senior data scientists in implementing predictive modeling solutions and ensuring data quality for effective modeling.

Responsibilities:

• Assist in the preparation of data science models for access by external clients
• This includes restructuring R, JavaScript, Scala, and Python code for API and web access and developing the actual API interface/protocol
• Develop and enhance statistical and machine learning models for the applications in the insurance industry, including mortality, morbidity, persistency, fraud, consumer response, etc., for use internally or externally
• Provide internal and external clients with an expert review of vendor and client-generated models
• Assist/support in developing commercial applications of predictive models for use in underwriting, claims, experience study, risk management, and/or projections
• When presented with specialist datasets, carry out the full spectrum of data analysis, from the development of statistical analysis plans and design of the database schema, through data cleansing and into the creation of new insights and knowledge based on a thorough and deep statistical analysis of the data
• Develop subject matter expertise in predictive modeling and advanced data analytics in the insurance application
• Support clients as needed
• Collaborate with local offices in support of various predictive modeling projects
• Develop verbal and oral communication skills whenever possible
• Actively participate in other research-related initiatives

Requirements:

• Master's degree in Arts/Sciences (MA/MS) in Statistics, Computer Science, Information Systems, Business, Finance, Economics, Information Systems, Computer Science, or related field - Required
• 1+ years of software development experience
• 1+ year experience with statistical and machine learning modeling (GLM, Decision Trees, Time Series, Regression, NLP, etc.) - Required
• 1+ years of experience with statistical modeling or relevant experience in insurance or related industry - Required
• Advanced PC and technical skills, including statistical programs (ex. R, SAS, MATLAB, or Python), spreadsheets (VBA), and database applications (Access, Oracle, SQL or equivalent technology)
• Familiarity with R or Python for predictive modeling and automation
• Knowledge of R-shiny
• Knowledge of SQL, JavaScript, XML, JSON, and HTML
• Knowledge of AWS technologies, such as EC2, S3, and Dynamo
• Basic familiarity with Linux/UNIX command line access
• Knowledge in econometrics, statistics, math and/or computational finance
• Ability to quickly adapt to new methods, work under tight deadlines and stressful conditions
• Ability to work well within a team environment, participate in department/team projects and balance detail with departmental objectives
• Strong oral and written communication skills, demonstrating the ability to convey business terminology that is meaningful and well-received
• Strong ability to handle multiple projects simultaneously
• Ability to liaise with individuals across a wide variety of operational, functional and technical disciplines
• Master's degree in Arts/Sciences (MA/MS) or Ph.D. in Statistics, Computer Science, Information Systems, Business, Finance, Economics, Information Systems, Computer Science, or related field - Preferred
• Ability to translate business needs and problems into viable/accepted solutions
• Investigative, analytical and problem-solving skills
• Knowledge of actuarial concepts including mortality, morbidity, and persistency studies
• Knowledge of life, health, and/or annuity products
• Knowledge of life insurance underwriting
• Solid experience with Java or C#
• Solid experience with R or Python for predictive modeling
• Familiarity with Domino Data Lab
• Knowledge of insurance risk analysis