Lead Data Science Engineer

Baker Hughes, a global energy technology leader with operations in over 120 countries, is seeking a Lead Data Science Engineer to join their Process & Pipeline Services Software & Data Science team. This role represents an exciting opportunity to lead the development and deployment of cutting-edge data science applications in the energy sector.

The position requires a seasoned professional with 5+ years of experience in data science and machine learning, who will be responsible for bridging the gap between data science innovation and software engineering excellence. The role involves designing and implementing machine learning models for anomaly detection and signal processing, while ensuring their successful deployment into production environments.

As a Lead Data Science Engineer, you'll work at the intersection of data science and software engineering, building robust data pipelines and APIs that integrate with enterprise systems. The role demands expertise in Python, Java, and modern ML frameworks, along with a strong understanding of MLOps practices and containerization technologies.

The position offers an attractive benefits package including comprehensive medical care, education assistance, mental health resources, and flexible working arrangements. Baker Hughes promotes a culture of diversity and inclusion, investing heavily in employee development and well-being.

This is an ideal opportunity for a technical leader who wants to make a significant impact in the energy sector, working with cutting-edge technologies while mentoring junior team members. The role combines the excitement of solving complex technical challenges with the opportunity to contribute to the future of energy technology.

Working at Baker Hughes means joining a company with a rich history of innovation and a strong commitment to transforming the energy sector. The company's focus on making oil and gas operations safer, cleaner, and more efficient aligns with the growing need for sustainable energy solutions.