Director, Data Scientist (Long-Term Care LTC)
Wash, 213 Washington St., Newark, NJ, United States
Full Time Executive-level / Director USD 167K - 251K
Prudential Financial
Helping individuals and institutions improve their financial wellness through life & health insurance, retirement services, annuities and investment products.Job Classification:
Technology - Data Analytics & ManagementAre you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? The Global Technology & Operations team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at Prudential, you’ll unlock an exciting and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions.
As the Director, Long-Term Care (LTC) Data Scientist in the U.S. Businesses (USB) Service, Data and Technology organization, you will partner with LTC business leaders, Machine Learning Engineers, Data Engineers, Data Analysts and other professionals to build new analytics capabilities, machine learning models and GenAI solutions for our business. You will implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services. You will implement capabilities to solve sophisticated business problems, deploy innovative products, services and experiences to delight our customers! In addition to deep technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership attitude and a continuous learning focus to all that you do.
This role is based in our office in Newark, NJ. Our organization follows a hybrid work structure where employees can work remotely and from the office, as needed, based on demands of specific tasks or personal work preferences. This position is hybrid and requires your on-site presence on a reoccurring weekly basis at least 3 days per week.
Here is what you can expect in a typical day:
- Provide deep technical leadership to a portfolio of high impact data science initiatives. Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery. Remove complex technical impediments.
- Learn and understand business and customer needs when designing data science solutions.
- Manage team members in analyzing data and in designing, building, and deploying scalable and reusable AI solutions which drive business value. Sometimes apply hands-on experience to ensuring best-in-class model development. Mentor team members in technical skill development.
- Communicate clearly and concisely, in writing and verbally, all facets of model design and development. Continuously look for insights in models developed and generate new ideas for model improvement.
- Manage external vendors in the execution of parts of the data science development process.
- Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
- Bring a deep understanding of relevant and emerging technologies, give technical direction to team members and embed learning and innovation in the day-to-day.
- Provide guidance and expert insights throughout the Responsible AI process for both in-house developed and external vendors’ AI solutions.
- Work on significant and unique issues where analysis of situations or data requires an evaluation of intangible variables and may impact future concepts, products or technologies.
- Manage LTC AI product roadmap and support the ideation of new use cases associated with business goals in claims, customer experience, and wellness.
The Skills and expertise you bring:
- Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines
- Ability to lead independently with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization
- Ability to align data science initiatives with the business’s strategic goals and long-term vision
- Experience with agile development methodologies and Test-Driven Development (TDD)
- 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 new skills and knowledge on an on-going basis through self-initiative and tackling challenges
- Excellent problem solving, communication and collaboration skills
- Experience in the financial services and insurance industry is preferred but not necessary
Significant experience and/or deep expertise with several of the following:
- 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, interpreting and monitoring machine learning models
- Generative AI & Natural Language Processing: Experience with modeling and interpreting text analysis including NLP, LLMs (BERT, etc), and Generative AI. Experience in developing and deploying generative AI solutions, including design, fine-tuning, prompt engineering, performance measurement, and feedback loop. Experience in modern Gen AI technologies including RAG, LangChain, LangGraph, vector DB.
- Statistics and Computing: Exceptional understanding of: Multivariable Calculus, Linear Algebra, Differential Equations, 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 Acquisition and Transformation: Acquiring data from disparate data sources using API's and SQL. Transform data using SQL and Python. Visualizing data using a diverse tool set including but not limited to Python.
- 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: ModelOp, 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.
- Data Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured).
- AWS DevOps: Experience in the project development life cycle in an AWS environment. Familiar with development, QA, staging and production deployment stages.
- Programming Languages: Python, SQL
You’ll Love Working Here Because You Can
Join a team and culture where your voice matters; where every day, your work transforms our experiences to make lives better. As you put your skills to use, we’ll help you make an even bigger impact with learning experiences that can grow your technical AND leadership capabilities. You’ll be surprised by what this rock-solid organization has in store for you.
#LI-LR1 #LI-Hybrid
What we offer you:Prudential is required by state specific laws to include the salary range for this role when hiring a resident in applicable locations. The salary range for this role is from $167,400.00 to $251,000.00. Specific pricing for the role may vary within the above range based on many factors including geographic location, candidate experience, and skills.Market competitive base salaries, with a yearly bonus potential at every level.
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.
Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance. To find out more about our Total Rewards package, visit Work Life Balance | Prudential Careers. Some of the above benefits may not apply to part-time employees scheduled to work less than 20 hours per week.
Prudential Financial, Inc. of the United States is not affiliated with Prudential plc. which is headquartered in the United Kingdom.
Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, national origin, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law.
If you need an accommodation to complete the application process, please email accommodations.hw@prudential.com.
If you are experiencing a technical issue with your application or an assessment, please email careers.technicalsupport@prudential.com to request assistance.
Tags: A/B testing Agile APIs AWS Bayesian BERT CI/CD Classification Computer Science CX Data Analytics DevOps Econometrics Engineering Finance Generative AI Jenkins LangChain Linear algebra LLMs Machine Learning Mathematics MLFlow ML models Model deployment Model design NLP Physics Pipelines Prompt engineering Python RAG Responsible AI SageMaker SQL Statistics TDD Testing
Perks/benefits: 401(k) matching Career development Competitive pay Equity / stock options Health care Insurance Medical leave Parental leave Salary bonus Wellness
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