Senior ML Scientist (Optimization & Reinforcement Learning)

Job Summary : We seek a Senior ML Scientist to drive innovation in AI ML-based dynamic pricing algorithms and personalized offer experiences. This role will focus on designing and implementing advanced machine learning models, including reinforcement learning techniques like Contextual Bandits, Q-learning, SARSA, and more. By leveraging algorithmic expertise in classical ML and statistical methods, you will develop solutions that optimize pricing strategies, improve customer value, and drive measurable business impact.

Qualifications :

• 8+ years in machine learning, 5+ years in reinforcement learning, recommendation systems, pricing algorithms, pattern recognition, or artificial intelligence.
• Expertise in classical ML techniques (e.g., Classification, Clustering, Regression) using algorithms like XGBoost, Random Forest, SVM, and KMeans, with hands-on experience in RL methods such as Contextual Bandits, Q-learning, SARSA, and Bayesian approaches for pricing optimization.
• Proficiency in handling tabular data, including sparsity, cardinality analysis, standardization, and encoding.
• Proficient in Python and SQL (including Window Functions, Group By, Joins, and Partitioning).
• Experience with ML frameworks and libraries such as scikit-learn, TensorFlow, and PyTorch
• Knowledge of controlled experimentation techniques, including causal A / B testing and multivariate testing.

Key Responsibilities :