At a Glance
- Tasks: Develop machine learning models for power market forecasting and collaborate with traders.
- Company: Leading firm in the energy sector based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting role with potential for career advancement in a fast-evolving industry.
- Why this job: Join a dynamic team and make a real impact on renewable energy forecasting.
- Qualifications: Strong Python/MLOps experience and SQL knowledge required.
The predicted salary is between 60000 - 80000 £ per year.
Our client in London is seeking a Power Analyst – Data Scientist to develop and advance machine learning forecasting models for European power markets, collaborating with traders and data teams to improve forecasting accuracy and trading performance.
You will build forecasting pipelines, onboard new data feeds, monitor data quality, and enhance model features as renewable generation evolves, with strong Python/MLOps experience and SQL knowledge.
Power Markets Data Scientist: Time-Series Forecasting in London employer: Marlin Selection Recruitment
Join a dynamic and innovative Commodity Trading firm in London, where you will be part of a collaborative team dedicated to excellence in trade operations. The company offers a supportive work culture that prioritises employee growth through continuous learning opportunities and mentorship, ensuring you can advance your career while making a meaningful impact in the energy sector. With competitive benefits and a focus on work-life balance, this is an excellent opportunity for those looking to thrive in a fast-paced environment.
Contact Details:
Marlin Selection Recruitment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Power Markets Data Scientist: Time-Series Forecasting in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Power Markets Data Scientist: Time-Series Forecasting 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 Marlin Selection Recruitment, 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 Marlin Selection Recruitment. 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 Marlin Selection Recruitment
✨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 Marlin Selection Recruitment!
✨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.
