Senior Data Scientist (Information Technology)

Job Classification:

Technology - Data Analytics & Management

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? The Global Technology 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 a Senior Data Scientist in the Chief Data Office (CDO), you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries tasked with mining our industry-leading internal data to develop new analytics capabilities for our businesses. The role requires a rare combination of sophisticated analytical expertise; business acumen; strategic mindset; client relationship skills, problem solving; and a passion for generating business impact. This is an exciting opportunity to be a part of a strategic initiative that is evolving and growing over time! In addition to applied experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership demeanor 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 2 days per week.

Here is what you can expect in a typical day:

• Responsible for the hands-on development of advanced data science solutions comprising the portfolio developed by the PDS and the technical requirements specified by the SLDS. Perform hands-on data analysis, model development, model training, model testing.
• Write production-level code and partner with machine learning engineers to push development code into production.
• Continuously research new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques.
• 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.

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.
• 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.
• Ability to learn new skills and knowledge on an ongoing basis through self-initiative and seeking challenges.
• Excellent problem solving, communication and collaboration skills.

Applied experience with several of the following:

• Statistics and Computing: Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics. Knowledge of statistical techniques such as the use of descriptive, inferential, Bayesian statistics, survival analysis, causal inference, time series analysis, etc. to extract business insights and experimentation to solve business problems.
• Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms (GBM, Random Forest, Deep Learning, Reinforcement Learning, kNN). Expertise in the application of machine learning theory to building, training, testing, and monitoring machine learning models.
• 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.
• Data Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured).
• 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 $99,000.00 to $163,200.00. 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.