Digital Technology Specialist - Data Science

Role Overview

Digital Technology Specialist - Data Science at Baker Hughes. The role combines data science, machine learning, AI, and software engineering to solve complex business and operational challenges across the oilfield services industry.

Company Overview

Baker Hughes is a world-class oilfield services company. The organization is increasingly adopting AI-enabled and agentic ways of working, with people at the heart of what they do. The company has revolutionized energy for over a century and prioritizes rewarding those who embrace change.

Role Purpose

To identify, frame, and solve complex business and operational challenges using data science, machine learning, AI, optimization, and software engineering techniques. Success requires rapidly learning emerging technologies, collaborating across disciplines, and contributing throughout the entire solution lifecycle from problem framing and experimentation through deployment, operationalization, and continuous improvement.

Key Responsibilities

Solution Development & Deployment

• Identify, frame, and solve complex business and operational challenges using data science, machine learning, AI, optimization, and software engineering techniques.
• Design, develop, test, deploy, and maintain end-to-end data and AI solutions that create measurable business impact.
• Translate analytical concepts into scalable, reliable, and maintainable production systems.
• Contribute across the full solution lifecycle, including requirements discovery, experimentation, development, deployment, monitoring, and continuous improvement.

Collaboration & Stakeholder Management

• Collaborate with domain experts to incorporate operational context and business constraints into solution design.
• Work closely with data engineers and platform teams to ensure data quality, reliability, scalability, and observability.
• Communicate technical findings and recommendations effectively to both technical and non-technical stakeholders.
• Contribute actively within Agile teams operating across multiple locations, functions, and time zones.

Technology & Innovation

• Leverage modern AI-assisted development practices and emerging technologies to accelerate delivery while maintaining engineering rigor, quality, and governance.
• Evaluate new technologies, frameworks, and methodologies, adopting them where they provide meaningful business value.

Knowledge Management

• Document, share, and promote best practices that improve team effectiveness and technical excellence.

Qualifications & Experience

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Physics, Information Systems, or another STEM discipline.
• Minimum 4 years of professional experience in data science, machine learning, analytics, software engineering, or a closely related technical field.
• Demonstrated experience delivering solutions from concept through production deployment.
• Strong programming and software engineering fundamentals.
• Proven ability to learn and apply new technologies, frameworks, and methodologies in rapidly evolving environments.
• Experience in Oil & Gas, energy, industrial operations, manufacturing, or related sectors is strongly preferred.
• Understanding of operational workflows, reliability, production optimization, asset performance, or related industrial challenges is advantageous.

Skills & Competencies

Technical Expertise

• Strong proficiency in Python and experience developing production-quality software.
• Experience with TypeScript, Go, and/or Rust.
• Experience with AWS and Databricks.
• Experience with Git-based CI/CD pipelines.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Experience with machine learning, AI, optimization, statistical analysis, and data-driven decision-making.
• Familiarity with large language models (LLMs), generative AI, agentic systems, and AI application development.
• Understanding of software architecture, testing, deployment, monitoring, and operational excellence.
• Experience working with structured, semi-structured, and time-series industrial data.
• Strong data visualization, storytelling, and stakeholder communication skills.

Leadership & Collaboration

• Demonstrated ability to contribute effectively within cross-functional and geographically distributed teams.
• Strong critical thinking, systems thinking, and problem-solving capabilities.
• Ability to balance experimentation with disciplined execution.
• Experience working in Agile delivery environments.
• Ability to influence technical direction through evidence, collaboration, and demonstrated results.

Mindset & Ways of Working

• Embrace change and continuously learn in rapidly evolving technology environments.
• Innovate courageously and challenge conventional approaches when better solutions exist.
• Focus on delivering measurable business outcomes rather than solely producing technical outputs.
• Build trust through transparent communication, active listening, and effective collaboration across multidisciplinary and global teams.
• Create value for customers and stakeholders through practical, impactful solutions.
• Apply sound scientific, analytical, and engineering principles while balancing experimentation, rigor, and execution.
• Demonstrate ownership, accountability, and a willingness to see solutions through from inception to operational adoption.
• Approach ambiguity with curiosity and confidence, creating clarity where it does not yet exist.

Additional Information

Working Arrangements

• Flexible working hours available, allowing you to flex the times when you work in the day to help fit everything in and work when you are most productive.

Benefits

• Contemporary work-life balance policies and wellbeing activities.
• Comprehensive private medical care options.
• Life insurance and disability programs.
• Tailored financial programs.
• Additional elected or voluntary benefits.