Data Scientist

• Hands-on experience with Reinforcement Learning techniques such as Q-Learning, DQN, PPO, Contextual Bandits, and Markov Decision Processes (MDP).
• Strong background in Machine Learning, Predictive Modeling, Optimization, and Stochastic Modeling.
• Proficiency in Python and SQL.
• Experience with Databricks, Spark, or similar big data platforms.
• Experience building and deploying scalable ML models in production environments.
• Strong understanding of experimentation, simulation, feature engineering, and model validation.

Preferred:

• Experience in Collections, Credit Risk, Financial Services, FinTech, or Customer Analytics.
• Knowledge of TensorFlow, PyTorch, MLOps, AWS, Azure, or GCP.
• Experience with real-time decisioning systems and customer behavior analytics.

If you have a strong background in Reinforcement Learning and are interested in solving complex business problems using AI and Machine Learning, we'd love to connect.