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

Description

• Drive the development, deployment, and optimization of advanced machine learning models for financial applications, ensuring scalability, accuracy, and robustness.
• Optimize model efficiency, robustness, and compliance with regulatory guidelines.
• Build robust feature engineering pipelines by leveraging financial data sources, transactional datasets, and alternative data.
• Conduct model validation, back-testing, and performance monitoring, implementing adaptive strategies based on market conditions.
• Ensure model interpretability and risk mitigation, aligning with model risk management and governance frameworks.
• 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.
• Collaborate with quantitative researchers, financial analysts, and engineering teams to integrate models into real-time production environments.

Requirements

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

Benefits

• 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.
• Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.
• Market competitive base salaries, with a yearly bonus potential at every level.
• Company-funded pension plan.
• 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.
• 401(k) plan with company match (up to 4%).
• Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.

Training + Development

Interview process

Visa Sponsorship

Security clearance