Data Scientist

Baker Hughes

2d

About The Position

Senior Data Scientist Do you enjoy working with multiple teams to ensure on-time delivery? Would you like the opportunity to develop your career within a global energy company? Be part of a successful team We are a leader in flexible line construction and production. Our innovative physical and digital solutions increase efficiency, production and maximize reservoir value. Partner with the best As a Senior Data Scientist, you will be responsible for Leading the full ML lifecycle—from problem formulation and data acquisition to enterprise-scale deployment. Collaborating with product managers, engineers, and domain experts to translate business needs into scalable AI solutions that enhance efficiency and safety. Designing and implementing advanced models for time series forecasting, natural language processing (NLP) for unstructured data, and agentic AI systems for autonomous decision-making. Applying statistical and machine learning techniques (e.g., regression, Bayesian methods, deep learning). Developing and optimizing predictive models for use cases such as equipment health monitoring, reservoir modeling, and real-time operational analytics. Ensuring model performance, interpretability, and compliance with industry standards and ethical AI practices. Fuel your passion To be successful in this role you will: Have Master’s, or PhD degree from a recognized university in Data Science, Computer Science, IT, Applied Mathematics, Statistics, Engineering, or related disciplines. / Specialization (education and work experience) in data science or machine learning. Have 6+ years of data science experience, delivering production-grade solutions. Have expertise in time series modeling, NLP, and agentic AI frameworks. Have strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Be familiar with oil & gas datasets (e.g., drilling, production, SCADA, seismic) and domain-specific challenges. Have experience working in product teams, contributing to roadmap planning and feature development. Have knowledge of cloud platforms (AWS, Azure, or GCP) and MLOps best practices. Preferred to have experience with reinforcement learning, LLM fine-tuning, or multi-agent systems for industrial automation. Preferred to have experience with digital oilfield technologies, sensor data analytics, and real-time monitoring systems. Work in a way that works for you We recognize that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too. In this role, we can offer the following flexible working patterns: Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working with us Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work. We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other. Working for you Our inventions have revolutionized energy for over a century. But to keep going forward tomorrow, we know we have to push the boundaries today. We prioritize rewarding those who embrace change with a package that reflects how much we value their input. Join us, and you can expect: Contemporary work-life balance policies and wellbeing activities Comprehensive private medical care options Safety net of life insurance and disability programs Tailored financial programs Additional elected or voluntary benefits You will be eligible to participate in Company-sponsored benefit programs, including health & welfare programs and the Thrift Plan (401k). You will have a choice of coverage options that best suit your needs. Coverage options and contribution amounts are related to your benefit elections, base salary level, and specific requirements of each of these plans. This position is eligible for our comprehensive and competitive benefits package, which can be found here, and is further eligible for additional forms of compensation such as bonuses subject to the terms of the applicable benefit plans or policies. At Baker Hughes, we are transforming the future of energy. With operations in over 120 countries, we are developing and deploying industry-leading technologies and services to take energy forward. For more than a century, our inventions have revolutionized energy. Today, we are bringing our expertise to make oil and gas safer, cleaner, and more efficient. Our people are the trusted experts, relied on to solve customer challenges big and small. We invest in the health and well-being of our workforce, train and reward talent, and develop leaders at all levels to bring out the best in each other. We believe in creating an environment of diversity and inclusion, without bias. We know we are better when all of our people are developed, engaged, and able to bring their whole authentic selves to work. We're makers, inventors, and leaders who aren't afraid of the tough challenges. We believe pushing boundaries will help to lead the way for a new energy future.

Requirements

• Have Master’s, or PhD degree from a recognized university in Data Science, Computer Science, IT, Applied Mathematics, Statistics, Engineering, or related disciplines.
• Specialization (education and work experience) in data science or machine learning.
• Have 6+ years of data science experience, delivering production-grade solutions.
• Have expertise in time series modeling, NLP, and agentic AI frameworks.
• Have strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Be familiar with oil & gas datasets (e.g., drilling, production, SCADA, seismic) and domain-specific challenges.
• Have experience working in product teams, contributing to roadmap planning and feature development.
• Have knowledge of cloud platforms (AWS, Azure, or GCP) and MLOps best practices.

Nice To Haves

• Preferred to have experience with reinforcement learning, LLM fine-tuning, or multi-agent systems for industrial automation.
• Preferred to have experience with digital oilfield technologies, sensor data analytics, and real-time monitoring systems.

Responsibilities

• Leading the full ML lifecycle—from problem formulation and data acquisition to enterprise-scale deployment.
• Collaborating with product managers, engineers, and domain experts to translate business needs into scalable AI solutions that enhance efficiency and safety.
• Designing and implementing advanced models for time series forecasting, natural language processing (NLP) for unstructured data, and agentic AI systems for autonomous decision-making.
• Applying statistical and machine learning techniques (e.g., regression, Bayesian methods, deep learning).
• Developing and optimizing predictive models for use cases such as equipment health monitoring, reservoir modeling, and real-time operational analytics.
• Ensuring model performance, interpretability, and compliance with industry standards and ethical AI practices.

Benefits

• Contemporary work-life balance policies and wellbeing activities
• Comprehensive private medical care options
• Safety net of life insurance and disability programs
• Tailored financial programs
• Additional elected or voluntary benefits
• You will be eligible to participate in Company-sponsored benefit programs, including health & welfare programs and the Thrift Plan (401k).
• You will have a choice of coverage options that best suit your needs.
• Coverage options and contribution amounts are related to your benefit elections, base salary level, and specific requirements of each of these plans.
• This position is eligible for our comprehensive and competitive benefits package, which can be found here, and is further eligible for additional forms of compensation such as bonuses subject to the terms of the applicable benefit plans or policies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees