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- Tasks: Develop forecasting models and support analytics for trading decisions in energy markets.
- Company: Leading energy company in Greater London with a focus on innovation.
- Benefits: Competitive salary, career growth opportunities, and a dynamic work environment.
- Why this job: Make a real impact on trading strategies while working with cutting-edge data science techniques.
- Qualifications: University degree in STEM, strong Python and SQL skills, and familiarity with machine learning.
- Other info: Collaborate with a small, passionate data team in a fast-paced industry.
The predicted salary is between 36000 - 60000 £ per year.
A leading energy company in Greater London is seeking a Data Scientist to develop forecasting models and support analytics for trading decisions. The role involves collaborating with a small data team to enhance trading capabilities across commodity markets (gas, oil, LNG).
Candidates should have:
- a university degree in a STEM subject
- strong Python and SQL skills
- familiarity with machine learning frameworks like PyTorch
This dynamic role offers significant influence on trading strategy and career growth opportunities.
Energy Trading Data Scientist: Forecasting & Analytics employer: INEOS Energy
Contact Detail:
INEOS Energy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Energy Trading Data Scientist: Forecasting & Analytics
✨Tip Number 1
Network like a pro! Reach out to professionals in the energy trading sector on LinkedIn. A friendly message can open doors and give you insights into the company culture and what they really value in candidates.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your forecasting models or analytics projects. This is your chance to demonstrate your Python and SQL prowess, and it’ll make you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data scientists, especially those related to machine learning and trading strategies. Mock interviews with friends can help you nail your responses.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Energy Trading Data Scientist: Forecasting & Analytics
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you can use these tools to develop forecasting models and support analytics for trading decisions.
Tailor Your CV: Customise your CV to reflect the specific requirements of the Energy Trading Data Scientist role. Mention any experience with machine learning frameworks like PyTorch, as this will catch our eye!
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. We appreciate straightforward communication that gets to the heart of why you’re a great fit for our team.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our dynamic data team.
How to prepare for a job interview at INEOS Energy
✨Know Your Data Science Fundamentals
Brush up on your data science basics, especially in forecasting models and analytics. Be ready to discuss how you’ve applied Python and SQL in past projects, as well as any experience with machine learning frameworks like PyTorch.
✨Showcase Your Collaboration Skills
Since the role involves working closely with a small data team, be prepared to share examples of how you've successfully collaborated in previous roles. Highlight your ability to communicate complex ideas clearly and work towards common goals.
✨Understand the Energy Market
Familiarise yourself with the current trends in the energy market, particularly in gas, oil, and LNG trading. Being able to discuss how your analytical skills can enhance trading strategies will show your genuine interest in the role.
✨Prepare Thoughtful Questions
Have a few insightful questions ready for your interviewers. Ask about the company’s approach to data-driven decision-making in trading or how they envision the role evolving. This shows your enthusiasm and strategic thinking.
