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Baker Hughes

Senior Data Scientist

Reposted 4 Days Ago
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In-Office
4 Locations
Senior level
In-Office
4 Locations
Senior level
As a Senior Data Scientist, you will lead the ML lifecycle, collaborate on AI solutions, and develop predictive models for operational analytics.
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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

Top Skills

AWS
Azure
GCP
Python
PyTorch
Scikit-Learn
TensorFlow

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