The term 'Energy Data Scientist' means more than just a Data Scientist who works in an Energy Company. Given the skills that this Skool community teaches, what jobs does the Energy Data Scientist cover?

A new video has been uploaded in the Online Course 5.20 in the Classroom. This course focuses on option contracts for crude oil, where the underlying asset is the spot price. An option contract is signed between two parties/ companies . Every option contract applies to an asset . This asset is known as “underlying”. So this course is about option contracts that have the crude oil as their underlying asset. The company that owns the option contract can exercise it until it expires. There is no obligation to exercise it. This is why it is called “option contract”. The company will exercise it only if it makes economic sense ie if it makes a profit. The video focuses on the “volatility” concept of option contracts . The video explains that the spot price of crude oil follows a probability distribution called : lognormal distribution. The attached plot, explained in the video, visualizes this concept. It shows how higher volatility (the red line) creates a much wider range of possible spot price outcomes compared to lower volatility (the green line). So a higher volatility means that in the future , the spot price of crude oil is more uncertain than if the volatility was lower. So volatility is similar to uncertainty . And it is visualized as a probability distribution that is wider. This plot shows the spot price of crude oil one year from today. One year from today this price is uncertain . The spot price of oil follows the log normal distribution . This distribution has a different shape depending on the volatility . Here we look at values for volatility of 10%, 30% and 50%. This is a fundamental plot and analysis for any quantitive finance / energy career . This specific plot has been part of multiple interviews for years . This plot is analyzed in the video using simple language. If you have any questions please contact me. I want this concept to be as clear as possible .

If you are developing optimisation models, I'm curious what solvers do you prefer for your mathematical optimization models. Whether you're doing linear programming, mixed-integer, or nonlinear optimization.

A new industry report has been uploaded. You can find it in the Classroom, at 6.2. This report is about European gas prices. It mentions that they have dropped to their lowest level in 18 months, falling below €30 per megawatt hour. The report identifies 3 key factors that have caused this drop. One has to do with traders' expectations about the war in Ukraine. Another has to do with the temperature in Europe this winter. A third factor has to do with the shipping costs of LNG from the U.S. This report is valuable for anyone looking to understand how geopolitics, weather, and global shipping affect energy prices , whether you're an aspiring energy trader, an investor tracking commodity markets, or simply someone who wants to understand market dynamics .

Hi everyone, I’m a Senior Software Engineer with over 10 years of experience in the IT field. I’m currently working with a U.S. based client, focusing on building scalable and high-performance web applications. I’m excited to be here and look forward to connecting and learning with you all.