Senior ML Scientist (Optimization & Reinforcement Learning)

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.

Responsibilities :

Key Responsibilities :

• Algorithm Development : Conceptualize, design, and implement state-of-the-art ML models for dynamic pricing and personalized recommendations.
• Reinforcement Learning Expertise : Develop and apply RL techniques, including Contextual Bandits, Q-learning, SARSA, and concepts like Thompson Sampling and Bayesian Optimization, to solve pricing and optimization challenges.
• AI Agents for Pricing : Build AI-driven pricing agents that incorporate consumer behaviour, demand elasticity, and competitive insights to optimize revenue and conversion.
• Rapid ML Prototyping : Experience in quickly building, testing, and iterating on ML prototypes to validate ideas and refine algorithms.
• Feature Engineering : Engineer large-scale consumer behavioural feature stores to support ML models, ensuring scalability and performance.
• Cross-Functional Collaboration : Work closely with Marketing, Product, and Sales teams to ensure solutions align with strategic objectives and deliver measurable impact.
• Controlled Experiments : Design, analyze, and troubleshoot A / B and multivariate tests to validate the effectiveness of your models.

Requirements : Qualifications :

Skills :