Energy Analyst at Shell

What’s the role

• Shell Energy Europe & Environmental Products is seeking an Energy Analyst to work within the Market Analysis team to develop and improve our forecasting models.
• Accurate forecasting of market fundamentals is critical to improved decision making on the trading desk. The analysis team develop and run a wide range of forecasts, using different methods such as machine learning, optimisation. 

What you’ll be doing

• Shell Energy Europe is looking to hire a data scientist to support the Power Fundamentals team in building and productionising time series forecasting and optimisation models (stochastic optimisation, dynamic programming, LP/MILP models, etc).
• This person will have an enthusiasm to learn the inner working of the power market by working in close collaboration with domain experts. They must be able to understand the fundamentals of the power market and translate this into a mathematical model.
• This requires taking a pragmatic approach to model development, starting with a simple model, and iteratively adding complexity – driven by adding business value in a high-pace environment. This person must be a strong programmer, who is confident in productionising models in the cloud (Azure/AWS) and is comfortable in designing and implementing data ingestion and model deployment pipelines.

Responsibilities:

• Prepare, process, clean and visualize various kind of power, gas, and weather data sets to establish a basis of further analysis
• Develop, analyse, and conduct different approaches to forecasts different variables (Demand, wind, solar, prices)
• Statistical evaluation and validation of different types of forecasts
• Build the framework to deploy models in production that will be use every day for trading decisions
• Share this framework with the rest of the team to increase the performance of the rest of the team developments
• Participate to the conception and development of a computational environment which enable scalability and high computational power
• Develop in house optimisation models (stack models, dispatch models)
• Bring new ideas of models to improve the desk P&L
• Delegate and lead some models and infrastructures projects done by teams of high technical people in IT and modelling.

What you bring

• Have a graduate qualification in an analytical or science-based discipline e.g., engineering/maths/computer science and ideally a PhD in machine learning, optimisation or equivalent
• High knowledge for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Strong competencies in Python for data analysis using the python data science libraries (Pandas/NumPy/SciPy/Scikit-learn).
• Strong SQL skills for data retrieval, basic analysis, and data cleansing.
• Strong knowledge and application of object-oriented design and software best practices in Python
• Familiarity of cloud architecture, with a focus in deploying and hosting applications in a cloud environment.
• Self-starter who is commercially aware and value focused. Able to work with minimal supervision and guidance.
• Good communication skills to present new developments and facilitate acceptation by the team and the traders.

Ideally you would be proficient in a good selection of the following:

• Algorithmic complexity theory
• Parallelism & Concurrency
• Experience with messaging and or data streaming technologies such as Kafka, ActiveMQ, Azure Service Bus, and Azure Event Hubs.
• Have experience implanting algorithms and data-structures
• Have a good knowledge of linear algebra, calculus, and discrete mathematics