Data Scientist - Reinforcement Learning
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Apply to Data Scientist - Reinforcement Learning at EXL Talent Acquisition TeamJob details
- Location
- Jersey City or Philadelphia or
- Work type
- Hybrid
- Posted
- 2 days ago
- Apply on
- fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com
About this role
Key Responsibilities
• Design and develop Reinforcement Learning models to optimize collections strategies, customer treatment paths, and recovery outcomes.
• Build adaptive decisioning systems using techniques such as:
o Q-Learning
o Deep Q Networks (DQN)
o Policy Gradient Methods
o Contextual Bandits
o Markov Decision Processes (MDP)
• Develop sequential and behavioral models for customer engagement, repayment prediction, and collections prioritization.
• Apply stochastic modeling and probabilistic methods to optimize dynamic treatment strategies under uncertainty.
• Collaborate with business stakeholders to translate collections and risk management problems into scalable AI/ML solutions.
• Build and maintain machine learning pipelines in Databricks or similar distributed computing environments.
• Conduct experimentation, simulation, and offline policy evaluation to validate RL strategies before deployment.
Responsibilities
Preferred / Good-to-Have Skill
• Experience in collections, credit risk, customer analytics, or financial services domains.
• Familiarity with:
o Deep Learning frameworks (TensorFlow, PyTorch)
o MLOps and CI/CD workflows
o Real-time decision systems
o Cloud platforms such as AWS, Azure, or GCP
Qualifications
Must-Have Qualifications
• Strong experience in Reinforcement Learning and sequential decision-making systems.
• Hands-on expertise with:
o Reinforcement Learning algorithms (Q-Learning, DQN, PPO, Bandits, etc.)
o Markov Decision Processes (MDP)