Data Scientist, Reinforcement Learning

About the role

Pioneer the application of reinforcement learning (RL) and sequential decision-making to high-impact challenges across ExxonMobil's upstream, downstream, and commercial operations. Collaborate with engineers, scientists, and business stakeholders to turn complex operational and planning problems into deployable, production-grade RL solutions. Advance the organization's capabilities in reinforcement learning, decision optimization, and autonomous control as part of the Modeling, Optimization, and Data Science (MODS) team.

What you will do

- Design, develop, and deploy reinforcement learning solutions for real-world energy applications such as production optimization, process control, supply chain scheduling, drilling optimization, and resource allocation. - Formulate sequential decision problems by defining state spaces, action spaces, reward structures, transition dynamics, and operational constraints with domain experts. - Develop RL agents using model-free methods (e.g., PPO, SAC, TD3, DQN where appropriate) and model-based approaches, selecting methods based on problem requirements, safety, and data availability. - Build and use simulation environments and digital twins for offline training, policy evaluation, and validation before real-world deployment. - Apply safe and constrained RL techniques to ensure agents operate within operational and safety limits. - Integrate RL solutions with existing optimization, simulation, and control systems across real-time and planning use cases. - Partner with data scientists and ML engineers to operationalize solutions, including training pipelines, monitoring, retraining, and performance tracking. - Benchmark RL against traditional methods such as LP, MIP, heuristic search, MPC, and stochastic optimization to identify best-fit approaches. - Stay current with advances in offline RL, safe RL, multi-agent RL, hierarchical RL, and model-based RL. - Share knowledge, publish findings where appropriate, and mentor peers on RL best practices.

About you

Desired Skills: - Experienced AI/ML professional with strong expertise in reinforcement learning, sequential decision-making, optimization, and real-world deployment. - 5+ years of experience in AI/ML, optimization, or related fields, including at least 2 years in reinforcement learning, sequential decision-making, or optimal control. - Master's or PhD in Computer Science, Machine Learning, Operations Research, Control Theory, Robotics, Applied Mathematics, Engineering, or a related quantitative field. - Deep understanding of RL fundamentals, including MDPs, dynamic programming, temporal-difference learning, policy gradients, and actor-critic methods. - Proven experience building RL systems end-to-end, from environment and reward design through training, evaluation, and deployment. - Experience with simulation environments, digital twins, or system models. - Strong background in statistics, probability, optimization, control theory, and algorithm design. - Proficiency in Python, PyTorch and/or TensorFlow, plus RL tools such as Stable Baselines3, RLlib, and Gymnasium. - Strong communication and collaboration skills, including the ability to explain technical concepts to non-technical stakeholders. Preferred Skills: - Experience applying RL or decision optimization in industrial domains such as process control, robotics, autonomous systems, supply chain, energy systems, or operations research. - Familiarity with offline (batch) RL, safe RL, and multi-agent RL. - Knowledge of model-based RL, MPC, and hybrid RL-control approaches. - Understanding of classical optimization methods and how RL complements them. - Experience with physics-informed or hybrid mechanistic/ML modeling and domain-informed reward or constraint design. - Familiarity with platforms such as Azure ML, Azure OpenAI, Databricks, and MLOps tools such as MLflow or Weights & Biases. - Experience in the energy industry or other asset-intensive, safety-critical sectors.

Your benefits

An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life. - Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life. - Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match. - Workplace Flexibility: We have several programs such as “Flex your Day”, providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work. - Comprehensive medical, dental, and vision plans. - Culture of Health: Programs and resources to support your wellbeing. - Employee Health Advisory Program: Provides confidential professional counseling for you and your family, including tools and resources promoting mental health and resiliency at no additional cost to you. - Disability Plan: Income replacement for when you cannot work due to illness or injury occurring on or off the job. Enrollment is automatic and at no cost to you.