AI/ML Jobs

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Principal Data Scientist at Equinor ASA (Stavanger, Norway)

Are you interested in building great machine learning products that can help Equinor transform into a greener and more competitive energy company?

We are looking for a Senior Data Scientist to join our Data Science team within our Digital Centre of Excellence, as we seek to impact the entire organization with groundbreaking innovations and powerful improvements, alike. This includes transforming how we approach internal, and sometimes external, collaboration models and work practices. Clearly, this is in service of our true goal, which is to establish energy leadership, through innovation and creativity.

The role of the COO organisation is to drive consistent long term safe and efficient operational performance and value creation. The COO organisation is responsible for the corporate improvement programs and works closely with the line in continuously improving Equinor's performance.

We are Equinor, a broad energy company that is evolving to include a portfolio of renewables like wind, solar and more. In order to achieve our ambitions to become a sustainable, continuously successful organisation, Equinor has launched a technology roadmap which will extract value creation from innovations. Equinor’s goal is to be the value creation leader within our core operations. Our technologies will continue to improve safety, reduce the carbon footprint from our operations and enable new, future-oriented and sustainable business models. 

The full potential of information technology is yet to be learnt; and we need your passion and courage to explore, innovate and unlock the full capabilities of Equinor, through its people, processes and asset portfolio. 

The Data Science team is a key part of our digitalization efforts at Equinor.  For us, data science means delivering products that create high value. This means we need to think deployment, scale & speed from day one, allowing us to apply our solutions to new business use cases with marginal extra cost. This means that we need to master the whole development cycle and push prototypes fast into production using our data science platform. To achieve speed, we work in a startup mentality and ringfence our highly competent team of 25 data scientists to develop great and scalable products. 

Our team's task is to prototype new solutions, drive early adoption, productizing, and iteratively improving deployed software. You will contribute to this end-to-end, through building and improving machine learning models, scaling solutions to new domains, and general software development.   
We believe in diversity and are proud of the mix of educational backgrounds (half of the team has PhDs), geographical locations (we are in 6 different cities, 3 different countries), industrial backgrounds (we hail from 6 different industries), nationalities (we are 15 different nationalities) and genders (30% women share and growing).  

This ad is part of an ongoing recruitment. Applications will be looked into and handled on a continuous basis.

Job Description

As part of or leading a small team, you will:

• Work closely with business stakeholders to identify value and business needs and translate them into concrete problem statements that you and your team can deliver on.
• Source, wrangle, cleanse and analyze large amounts of data in our cloud-based development and production environment
• Rapidly prototype and iterate to build production ready solutions that scale with minimal cost, building on existing internal services or developing new ones
• Identify and build the right user experience so that the output of your ML workflows is easily interpretable for and actionable by the business users 
• Tune your models / architecture efficiently
• Embed your ML workflows as part of existing or new Equinor ML products, refactor your code to meet our deployment standards
• Improve and develop machine learning models using state-of-the-art techniques within deep learning
• Monitor and follow-up your models when in production to ensure good performance & value creation 


• PhD or Master in Computer Science, Statistics, Applied Mathematics, Engineering or equivalent fields
• Experience developing and productizing real-world AI/ML applications such as prediction, personalization, recommendation, optimization and content understanding
• Experience in ML/AI product development and iterative work: from data generation/collection to visualization and explainability 
• Experience working with any of the following machine learning frameworks / libraries: sklearn, tensorflow, keras,
• Preferred experience within NLP, semantic technologies and graph technology with understanding of fundamental linguistic and grammatical concepts and their use in NLP applications
• Preferred experience creating ML workflows on sequences and timeseries with experience in applying signal processing and or spectrum analysis
• Preferred experience working with large data sets using open source technologies such as Spark, Hadoop, and Neo4j
• Coding skills in Python, experience with containerization and micro-services development
• Good communication skills  
• Relevant experience may compensate for formal qualifications.
• 5-7 years of relevant experience preferred. 

Personal Qualities

To succeed within the data science team, you will need to be motivated by creating impact using ML, be willing to take ownership and responsibility for your work, work autonomously, and have the humility to receive feedback and identify your learning opportunities.
• You are outcome driven and can handle uncertainty
• You are above average curious, driven to ensure that you fully understand the business context of your solution
• You believe in fast prototyping, evaluating, changing course when you feel that you are going down a dead end
• You have curiosity beyond ML modeling. You are excited about end-to-end aspects of deploying ML models
• You are innovative, analytical and base your judgements on data
• You take ownership of your learning and development and constantly seek challenging opportunities

Ability to live by our safety and security expectations.

We Offer

Not just a job: a career. We encourage you to take advantage of the many opportunities our global company offers, and empower you to build your career across multiple disciplines and geographies, exchange ideas and learn from others.

Rewards. We offer a range of reward programmes within one Equinor framework adapted to the local market. This includes competitive salary, variable pay schemes and a share savings plan. 

Wellness and work-life balance. Our employees’ health and well-being is a priority and we encourage our people to make use of our flexible work arrangements to help balance their work and home lives efficiently. 

An inclusive culture. Embracing an inclusive culture is a fundamental part of our values, and leveraging our diverse perspectives and experiences help us deliver together.

General Information

Would you like to  know what our data scientists are working with? Read the story of our colleague Bjarte Johansen here.

Make sure that we are able to give your application consideration: Please attach copies of your diplomas, certificates and grades in English or Norwegian (or another Scandinavian language). Applications submitted without such attachments will unfortunately not be evaluated. If you are in the process of completing a degree, please upload an official temporary transcript or other document describing subjects and grades completed to this point.

Our values are to be courageous, open, collaborative and caring. We believe in these qualities, which are essential for building an even stronger Equinor. If you can identify with them, you could be the one to strengthen our team.

Candidates are expected to openly offer all relevant information about themselves during the recruitment process.

All hires will be screened against relevant sanctions lists to ensure compliance with sanctions law and increase security.

If you have questions about the position or the process please send an email to

Please be aware that no applications or attachments to applications will be accepted via email.

Title and discipline band will be decided based on the candidate's experience.