About the role

Data Scientist at PGIM developing machine learning models and insights for financial applications. Collaborating across teams to elevate business outcomes in asset management with a hybrid work model.

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.

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

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