Prudential Financial · 4 hours ago
Senior Data Scientist
Newark, NJ
Full-time
Hybrid
Mid, Senior Level
$97K/yr - $179K/yrPrudential Financial is one of the world’s leading financial services institutions, and they are seeking a Senior Data Scientist to support Group Insurance in the GRI Technology organization. The role involves developing analytics capabilities by collaborating with a diverse team to mine internal data and create sophisticated data science solutions.
Asset ManagementFinanceFinancial ExchangesFinancial ServicesHealth CareInsuranceRetirement
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 productionize 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
Qualification
Required
Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines
Working on complex problems in which analysis of situations or data requires an in-depth evaluation of various factors. Exercises judgment within broadly defined practices and policies in selecting methods, techniques, and evaluation criteria for obtaining results
Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business
Experience in research and designing experiments (ex: A/B testing). An insurance actuary background is preferred but not required
Ability to learn creative skills and knowledge on an on-going basis through self-initiative and solving challenges
Excellent problem solving, communication and collaboration skills
Data Acquisition and Transformation: Acquiring data from disparate data sources using API's, SQL and NoSQL. Transform data using SQL, NoSQL, and Python. Visualizing data using a diverse tool set including but not limited to Python and R
Database Management System: Knowledge of how databases are structured and function in order to use them efficiently may include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc
Model Deployment: Understanding of: MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc. model and data versioning
Statistics and Computing: Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science (Programming Methodologies), and Cloud. Knowledge of statistical techniques such as the use of descriptive, inferential, bayesian statistics, time series analysis etc. to extract business insights and experimentation to solve business problems
Data Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured)
Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, and monitoring machine learning models. Understanding and expertise in NLP (natural language processing)
Programming Languages: Python, R, SQL, Java or Scala, SQL, Cypher
Benefits
Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.
401(k) plan with company match (up to 4%).
Company-funded pension plan.
Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.
Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.
Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.
Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service.
Company
Prudential Financial
Prudential Financial specializes in the fields of investment management, life insurance, and retirement benefits. It is a sub-organization of Prudential Financial.
Founded in 1875
10001+ employees
H1B Sponsorship
Prudential Financial has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2024 (1)
2023 (1)
Funding
Current Stage
Public CompanyTotal Funding
$1.25BKey Investors
AM Best
2025-03-13Post Ipo Debt· $750M
2024-02-14Post Ipo Debt· $500M
2001-12-13IPO
Leadership Team
Andrew Sullivan
Chief Executive Officer
Yanela Frias
Executive Vice President & Chief Financial Officer
Recent News
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2026-01-19
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2025-12-18
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