Remote ML Ops Data Scientist for Energy Analytics

Siemens Energy; Porto; On-site; EUR 50,000 - 70,000; Full time

Benefits offered by this job

Health insurance coverage

Meal allowance

Remote work within Portugal

Pontes days off and Birthday off

Job summary

Siemens Energy is seeking a Data Scientist (Machine learning Ops) to join the Digital Services unit within Gas Services. You will work on challenging analytics projects across the energy industry, driving data value and developing analytics solutions that support data-driven decisions.

You will contribute to advanced analytics, ML/AI concepts, and cross‑functional collaboration while leveraging AWS SageMaker and cloud services in a global, multicultural environment.

Qualifications

• Experience in Data Science, Machine Learning and AI.
• Proficiency in Python and/or R for modeling and analysis.
• Experience deploying analytics models using Docker and cloud services.
• Familiarity with AWS SageMaker and data warehousing is advantageous.

Responsibilities

• Develop advanced analytics solutions across the value-chain as part of a global team.
• Create data mining architectures and models to identify patterns in diverse datasets.
• Design and develop AI concepts addressing customer challenges.
• Apply tools and methods across various business areas to maximize impact.
• Document methods and project results; present findings to the ED&AA global team.
• Collaborate in multidisciplinary environments and drive data value across the organization.

Skills

AWS SageMaker

Python

R

Statistical modeling

Machine Learning / AI

Serverless technologies

Tools

Docker

Job description

Siemens Energy is seeking a Data Scientist (Machine learning Ops) to join the Digital Services unit within Gas Services. You will work on challenging analytics projects across the energy industry, driving data value and developing analytics solutions that support data-driven decisions.

You will contribute to advanced analytics, ML/AI concepts, and cross‑functional collaboration while leveraging AWS SageMaker and cloud services in a global, multicultural environment.