The Global Technology team at Prudential is looking to build capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency, specifically in the area of data analytics and management for Group Insurance in the GRI (Global Retirement & Insurance) Technology organization.
Requirements
- Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines.
- Experience in research and designing experiments (ex: A/B testing).
- Applied experience with several of the following: Data Acquisition and Transformation, Database Management System, Model Deployment, Statistics and Computing, Data Wrangling, Machine Learning, Programming Languages: Python, R, SQL, Java or Scala, SQL, Cypher
- Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business.
- Ability to learn creative skills and knowledge on an on-going basis through self-initiative and solving challenges.
- Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science (Programming Methodologies), and Cloud.
- Understanding of machine learning theory, including the mathematics underlying machine learning algorithms.
Responsibilities
- Responsible for the hands-on development of sophisticated data science solutions comprising the portfolio developed by the Lead Data Scientist and Actuaries and the technical requirements specified by the Lead Data Scientist and Actuaries.
- Perform hands-on data analysis, model development, model training, model testing, model deployment.
- Continuously research new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques.
- Write production-level code and partner with machine learning engineers to push development code into production.
- Partner with machine learning engineers to productionized machine learning models. Partner with data engineers to build data pipelines. Partner with software engineers to integrate solutions with business platforms.
- Work closely with the business and data science lead to recommend and develop models for GI financial underwriting, medical underwriting, marketing analytics and other business use cases.
- Manage external vendors in the execution of the data science development process.
Other
- Excellent problem solving, communication and collaboration skills.
- Ability to work in a hybrid environment with on-site presence required at least 3 days per week.
- Advanced degree (Masters, Ph.D.) in a relevant field.
- Travel requirements not specified, but may be required based on business needs.
- Must be eligible to work in the United States, with no visa sponsorship available.
