Data Scientist

Overview

Design, develop, and deploy advanced AI/ML solutions across multiple domains.

Key Responsibilities

• collaboration
• genai development
• mentoring
• mlops
• solution delivery
• data governance

Tasks

-Collaborate with cross-functional teams to translate business problems into mathematical frameworks. -Develop GenAI applications (chatbots, copilots, multi-agent workflows) and/or time series, optimization, or commercial analytics models. -Mentor peers and contribute to internal AI capability building. -Ensure production readiness through MLOps practices (CI/CD, MLflow, monitoring, cost optimization). -Lead end-to-end delivery of AI/ML solutions: scoping, modeling, evaluation, deployment, and monitoring. -Build solutions in one or more domains listed above, applying best practices for data quality, explainability, and governance.

Requirements

• python
• pytorch
• azure ml
• mlops
• phd
• 5+ years

What You Bring

-Subsurface & Wells (physics-informed ML, production optimization) -Optimization & Prescriptive Analytics -Familiarity with GenAI frameworks (LangChain, Promptflow) and/or optimization libraries. -Excellent communication and collaboration skills. -Computer Vision & Document Intelligence -Commercial Analytics (pricing, marketing, supply chain) -Generative AI & NLP (LLMs, agentic workflows) -Strong foundations in statistics, probability, and algorithm design. -Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn) experience with Databricks/Spark. -Knowledge graphs, hybrid search/RAG, and semantic technologies. -Cloud platforms (Azure ML, Azure OpenAI, Databricks). -5+ years of direct experience delivering production AI/ML solutions. -Commercial domain experience (pricing, forecasting, supply chain) or energy/subsurface expertise. -Agile development and software engineering best practices. -Expertise in one or more of the following: NLP/GenAI, time series, optimization, commercial analytics, subsurface/wells, computer vision. -Master’s or PhD in Data Science, Computer Science, Engineering, Applied Math, or related field. -Experience with MLOps, model governance, and explainable AI techniques (e.g., SHAP, LIME).

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Benefits

-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. -Comprehensive medical, dental, and vision plans. -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. -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. -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.

About Exxonmobil

-Driving global energy innovation through extensive operations in oil and natural gas exploration and production.

Sector Specialisms