About this role
Cognite develops industrial AI and data solutions focused on solving complex challenges across sectors such as oil and gas, power and utilities, and manufacturing. The engineering team builds scalable digital applications, physical models, and machine learning architectures using the core industrial dataops platform to accelerate customer digital transformation.
In this role, the incoming professional collaborates directly with cross-functional peers including data engineers, solution architects, and project managers to configure, deploy, and operationalize industrial use cases. Responsibilities include leading design workshops with subject matter experts, writing production-ready code, and applying generative artificial intelligence techniques to enhance operational decision-making.
Candidates who thrive in this environment possess a strong background in quantitative fields, extensive experience deploying data models in production, and a readiness to operate independently while mentoring teammates. A successful team member appreciates complex industrial problems and shares the overarching ambition to unlock measurable value for global industrial operations.
What you will do
- Lead the design and development of scalable solutions for customer use cases across manufacturing, oil and gas, and utilities sectors.
- Facilitate intensive use case generation workshops with subject matter experts to map problem statements to available data.
- Perform data cleansing, exploratory data analysis, and implement physical or machine learning models using Python.
- Apply generative AI techniques and build web applications on top of the company data fusion platform.
- Collaborate closely with data engineers, project managers, and solution architects to deliver project goals.
- Support external customers and partners in executing data science tasks utilizing company products.
What you need
- Hold a Bachelor or Master of Science degree in a quantitative discipline or mechanical, systems, electrical, or industrial engineering.
- Bring at least 6 years of full-time professional experience working as a data scientist.
- Demonstrate proficiency in Python and SQL for development tasks.
- Possess solid familiarity with machine learning methods, statistics, and optimization techniques.
- Have hands-on experience using Git version control in professional settings.
- Show proven capability working directly with external customers in client-facing capacities.
Nice to have
- Domain knowledge or understanding of the oil and gas industry
- Asset performance management experience covering production optimization
- Experience using Python in a production setting
- Experience with managed cloud services such as GCP, Azure, or AWS
Benefits
- Private health services with Cognite Care
- Subsidized lunch at the canteen delivered by chefs at Fornebuporten
- Access to an exclusive on-site coffee bar
- Free membership to a fully-staffed gym on-site and broad health offerings
- An international work environment featuring 60 different nationalities
Skills and tech stack
Questions candidates ask
What industries does the data science team build solutions for?
The team configures, deploys, and operationalizes digital solutions in sectors such as oil and gas, energy, power and utilities, and manufacturing.
What tools and technologies are used in this role?
Professionals use Python, SQL, Git, managed cloud services like GCP, Azure, or AWS, and build applications on Cognite Data Fusion.
What are the primary job duties for this position?
Key tasks include leading design workshops with subject matter experts, performing exploratory data analysis, implementing machine learning models, and applying generative AI techniques.
What kind of professional background is required?
Applicants must have a bachelor or master of science in a quantitative or engineering field alongside at least six years of full-time work experience as a data scientist.
The application is on the official Cognite - AI for Industry careers page.
Apply on company site