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At INEOS Energy we produce and trade oil, gas, power, liquefied natural gas (LNG) and carbon credits. This is supported by our investments in low carbon technologies, which will help sustain our business through the energy transition. Direct examples of these areas are ‘Project Greensand’, our pioneering carbon storage project in the Danish North Sea and our investment in HydrogenOne Capital.

As Machine Learning Data Scientist you will be responsible for implementing and deploying machine learning models in production environments, working with complex datasets, and using available tools and services. Additionally, you will play a key role in enhancing our data infrastructure by supporting the design and construction of robust databases and developing data pipelines.

Responsibilities and Accountabilities

Machine Learning

You will be actively involved in identifying and delivering opportunities where machine learning can drive impactful business solutions across our Subsurface, Operations and Trading departments.

• Collaborate with cross-functional teams to identify business problems and opportunities to develop ML solutions.
• Work on building and refining machine learning models to address specific business challenges.
• Utilise a range of algorithms and techniques, such as regression, classification, clustering, and deep learning, to develop predictive and prescriptive models.
• Collaborate with data engineers to deploy machine learning models into production environments on Azure/AWS.
• Integrate machine learning solutions with existing business systems to maximise their impact on business operations.
• Develop and maintain technical documentation and best practices.
• Stay up-to-date with the latest developments in machine learning, AI and related technologies.

Database Support

As part of the initial phase, you will work closely with our data engineers and data analysts to support the design and construction of databases and key ETL architecture for our Trading team.

• Collaborate with the data team to design and implement a scalable and high-performance database infrastructure.
• Develop ETL pipelines to extract, transform, and load data from various sources into the database.
• Ensure data integrity, quality, and consistency throughout the ETL process.
• Familiarity with data pre-processing and data transformation techniques.

Skills & Knowledge Required

Technical Skills

• Bachelor's or Master's degree in Computer Science, Statistics, Data Science, or related fields with 0-3 years of experience in data science and machine learning,
• Proficient programming skills in languages such as Python or other programming languages.
• Experience with database management and data processing tools.
• Familiarity with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Previous experience with real-world applications would be advantageous.

Behavioural skills

• Strong problem-solving skills and analytical thinking.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.