Data Scientist (GenAI/ML)

at  Shell

WHERE YOU FIT IN

Shell’s global Trading and Supply business is one of the largest energy trading operations in the world with key hubs in Singapore, Dubai, Houston, London, and Rotterdam, trading in crude oil, natural gas, LNG, electrical power etc. Our business in Asia has set huge growth targets for the coming years with major focus on green and sustainable energy.
To accelerate our ambitious delivery goals and energy transition targets in Asia, our gas and power trading division in the region is looking for highly skilled and motivated Data Scientist with expertise in Generative AI and Machine Learning to join our dynamic team

WHAT WE NEED FROM YOU

To be successful in this role, we need someone who is an analytical problem solver, is excited about analytical models and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders.

Furthermore, we hope to see the following:

• 5 years of track record in developing and deploying machine learning algorithms with proven business impact
• Experience with Generative AI and Large Language Models
• Expertise in languages and similar software such as Python, SQL, Azure ML and Databricks
• Story telling of Machine Learning models to business users
• Agile Delivery techniques (e.g. SCRUM), user stories, tools such as Azure DevOps
• Can explain software engineering best practice e.g. CI/CD, 12-factor, git branching strategies, test automation
• Experience in time series analysis / predictive modelling with low granularity time series data, preferably in a commodity or financial trading domain is an advantage

If you don’t see yourself reflected in the job requirements on the posting above, we still encourage you to reach out and apply. Shell is committed to creating a more diverse, equitable and inclusive workplace and we encourage individuals of all backgrounds to send in your applications.

COMPANY DESCRIPTION

Shell is an international energy company that uses advanced technologies and takes an innovative approach to help build a sustainable energy future. Here in Singapore, Shell has a long history and is one of the country’s largest foreign investors. It has businesses spanning trading and marketing of liquefied natural gas; refining, trading, marketing and shipping of oil products, lubricants and chemicals; low carbon solutions; and operating a network of service stations through retailers, as well as electric vehicles charging.

Your accountabilities will also include:

• Developing AI solutions to business challenges with business analysis
• Write clean and maintainable production-level code, knowledge on: Python, Databricks, GIT, SQL, Azure ML
• Enhance machine learning models on ad-hoc basis.
• Work closely with the customer and the Product Owner day-to-day
• Work in a highly-collaborative, friendly Agile environment, participate in Ceremonies and Continuous Improvement activities.
• Documenting and explaining the results of analysis or modelling to both a technical and non-technical audience
• Learning new engineering practices, technologies and continuously improving our Agile practice

We are looking for people with the ability to translate business problems into AI solutions. This requires that you have next to your knowledge of machine learning and/or statistics as well as a good grasp of software development. Next to the data science capabilities and experiences you should be able to clearly and effectively present findings to our colleagues in other areas of expertise and business stakeholders.
The ideal candidate has strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning, GenAI) and has applied those skills in solving real world problems across different businesses / functions.

Your accountabilities will also include:

• Developing AI solutions to business challenges with business analysis
• Write clean and maintainable production-level code, knowledge on: Python, Databricks, GIT, SQL, Azure ML
• Enhance machine learning models on ad-hoc basis.
• Work closely with the customer and the Product Owner day-to-day
• Work in a highly-collaborative, friendly Agile environment, participate in Ceremonies and Continuous Improvement activities.
• Documenting and explaining the results of analysis or modelling to both a technical and non-technical audience
• Learning new engineering practices, technologies and continuously improving our Agile practices