At a Glance
- Tasks: Develop and deploy forecasting models for power market dynamics using Python and SQL.
- Company: Join Shell Energy, a leader in energy innovation and sustainability.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Fast-paced environment with collaboration across teams and excellent career advancement.
- Why this job: Make a real impact on the future of energy with cutting-edge data science.
- Qualifications: Experience in data science, time series forecasting, and strong analytical skills.
The predicted salary is between 63000 - 77000 £ per year.
Shell Energy Europe & Environmental Products is seeking a Data Scientist to join the Market Analysis team to develop and productionise time series forecasting and optimisation models for power fundamentals. You will translate power market dynamics into mathematical models and deploy them in the cloud, collaborating with domain experts and traders. You will build data pipelines, validate forecasts, and iterate toward business value in a fast-paced environment, using Python, SQL, and modern ML.
Power Market Forecasting Data Scientist in London employer: Shell
At Shell, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through comprehensive training programmes and opportunities for advancement within the company. Located in a vibrant environment, we provide our team with unique advantages such as flexible working arrangements and a strong focus on sustainability, making Shell not just a workplace, but a community dedicated to meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Power Market Forecasting Data Scientist in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Power Market Forecasting Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Shell, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Shell. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Shell
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Shell!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
