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Selected role

Senior Data Scientist - PGIM Global Services (Hybrid - Newark, NJ)

PGIM Newark, NJ, US

Senior Full-time

Job Classification:

Technology - Data Analytics & Management

As the Global Asset Management business of Prudential, we’re always looking for ways to improve financial services. We’re passionate about making a meaningful impact - touching the lives of millions and solving financial challenges in an ever-changing world.

We also believe talent is key to achieving our vision and are intentional about building a culture on respect and collaboration. When you join PGIM, you’ll unlock a motivating and impactful career – all while growing your skills and advancing your profession at one of the world’s leading global asset managers!

If you’re not afraid to think differently and challenge the status quo, come and be a part of a dedicated team that’s investing in your future by shaping tomorrow today. At PGIM, You Can!

PGIM Data Science is a newly established team and you will join it as key founding member. As the Data Scientist for PGIM, you play a pivotal role in shaping and executing PGIM’s data-driven strategy, specifically in asset management area. You will partner with other cross-functional teams, data engineers, financial analysts and business leaders to shape the future of PGIM’s data landscape. This role closely engages with the development of advanced data science projects and data driven insights to significantly elevate business outcomes. You will solve meaningful business problems using advanced machine learning models.

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 3 days per week and can change based on future updates to the company’s in-office presence policy.

Responsibilities

Drive the development, deployment, and optimization of advanced machine learning models for financial applications, ensuring scalability, accuracy, and robustness.
Design and implement machine learning models, including regression, classification, clustering, time-series forecasting, natural language processing (NLP) and reinforcement learning for cross-divisional asset management mandate.
Build robust feature engineering pipelines by leveraging financial data sources, transactional datasets, and alternative data.
Ensure model interpretability and risk mitigation, aligning with model risk management and governance frameworks.
Conduct model validation, back-testing, and performance monitoring, implementing adaptive strategies based on market conditions.
Collaborate with quantitative researchers, financial analysts, and engineering teams to integrate models into real-time production environments.
Optimize model efficiency, robustness, and compliance with regulatory guidelines.

Qualifications

A minimum of a Master’s degree in Statistics, Data Science, Applied Mathematics, Computer Science, or comparable quantitative disciplines. PhD is preferred.
1+ years of working experience in advanced machine learning techniques, including:
Reinforcement Learning (Q-learning, deep Q-networks, policy gradient methods)
Natural Language Processing (text embeddings, topic modeling, entity recognition, transformer-based models for financial document analysis)
Hands-on experience in back-testing, and performance evaluation and monitoring of the models in asset management industry
Preferably hands-on experience in developing LLM, NLP, NLU, NLG, deep learning models, and transformer models, with a focus on developing conversational AI solutions.
Proficiency in Python, R, SQL, and the corresponding machine learning libraries.
Preferably strong knowledge of machine learning application in financial industry, but not required.
Experience in deploying ML models into production, optimizing for efficiency, scalability, and interpretability.
Excellent documentation, communication and presentation skills, can influence without authority
Team-orient mindset and can-do attitude

What we offer you:

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

[email protected]

If you are experiencing a technical issue with your application or an assessment, please email

[email protected]

to request assistance.

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