Developing and implementing a long-term forecasting algorithm
Improving the platform's existing capabilities
Forecasting and performing simulations of factors affecting the price
Working with the developers to create workflows that allow clients to maximise their efficiency across day ahead and intraday markets
Running and continuously improving existing price forecasting, models, databases and methodology
Monitoring and assessing market and regulatory developments including reports, reviewing and challenging external consultant forecasts
Maintaining and regularly reviewing market data and input assumptions
Producing price forecasts and scenarios, and providing expert insight for optimisation, hedging, budgeting and investment/business development decisions.
Requirements :
Masters or PhD in Data Science with a Finance background
Python and its data science libraries (NumPy, SciPy, pandas, seaborn, Scikit Learn, matplotlib, Python/Jupyter)
R, Python, Azure, Power BI
Coding experience to develop the models. This will likely be in a statistically driven programming language such as Python or R
Expertise in Machine Learning, Deep Learning and Statistics is desirable
Solid experience working with large volumes of data, big data architecture and data flows
Proven experience in the energy industry with a specific focus on having developed forecasting models
Proven track record of developing forecasting models that have been successfully implemented in industry and used to determine investment decisions
Ability to demonstrate value from your previous projects
A demonstrable ability to effectively communicate with both technical and non-technical audiences.