Job Detail

Job Description

We have an exciting opportunity for a Data Science Researcher to join Shell’s Data Science organization. Be part of a team focused on developing end-to-end process maintenance solutions and contribute in delivering value for our customers, and for Shell.

Where you fit

Shell’s Projects and Technology (P&T) business exists to make the delivery of our strategies and the growth of our company possible. Our team develops the advanced products and technologies Shell needs to meet customer demand. Our solutions help our partners grow the LNG, Gas and Power businesses, deepen the integration of Manufacturing, Chemicals and Trading, and maxmise the competitiveness of our Upstream business.

As Data Science Researcher, you will work hands-on across project teams focusing on research and implementation of Data Science models on different Shell Assets working closely with the field engineers solving real problems.

What’s the role?

As a Data Science Researcher, your responsibilities are as follows:

• Apply your knowledge of Data Science to a variety of problems like predictive analytics, asset integrity, process optimization, remaining useful life estimation, prediction and forecasting.
• Gather, integrate, and analyze large data sets and use statistical analysis to support decision making.
• Evaluate data science methods and procedures used to ensure applicability, efficiency, accuracy, and validity of analyses.
• Research new ideas and stay up to date with the world of AI/ML.
• Propose and develop innovative designs and analysis methods and evaluate them via simulation studies.
• Proactively work with other product teams and internal stakeholders across different use cases.
• Consult and convey statistical modeling results as well as business impact to internal and external business partners.
• Share knowledge and expertise with the team.
• Collaborate to create intellectual property such as white papers, articles, and patents.

What we need from you

• Master's Degree or PhD in relevant discipline such as Statistics, Mathematics, Computational Science, Computer Science, Physics or related fields.
• Significant commercial experience building ML and AI models both using traditional ML approaches as well as Deep Learning.
• Solid foundation in Statistics and Mathematics (Linear algebra, probability theory, Bayesian statistics, etc.)
• Working knowledge of main ML libraries and frameworks (e.g., tensorflow, sckit-learn, pyTorch).
• Hands-on experience with ML cloud services such as AzureML and/or AWS Sagemaker.
• Excellent software programming skills in object-oriented programming framework.
• Able to write clean, well-documented code in Python.
• Experience across the project life cycle, from ideation to delivery.
• Excellent communication skills (both technical and non-technical audiences) and the ability to work in a team

Skills Required

• pythan