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- Tasks: Develop forecasting models and support analytics to drive trading decisions.
- Company: Join INEOS Energy Trading, a leader in the energy market.
- Benefits: Dynamic role with career growth opportunities and impactful projects.
- Why this job: Shape the future of data-driven trading in a small, agile team.
- Qualifications: University degree in STEM, strong Python and SQL skills required.
- Other info: Work onsite at our Knightsbridge office and collaborate closely with a Data Engineer.
The predicted salary is between 36000 - 60000 £ per year.
INEOS Energy Trading operates as the single face to the Gas, LNG, Power, Carbon, and Crude Oil commodity markets for INEOS. Our core mission is to fully monetise INEOS Energy’s equity Oil and Gas production across Europe and the US. Beyond this, the Trading and Business Development teams are tasked with originating and developing complementary third-party physical business. We also support the wider INEOS group by leveraging our carbon trading capabilities and supplying LNG, Gas, and Power to INEOS’s industrial base. Our team is on an exciting growth journey, and we anticipate continued growth across both new commodities and geographies, as the business evolves to support INEOS Energy’s expanding global footprint.
We are seeking a Data Scientist to join our small, dynamic data team. This role involves developing forecasting models, maintaining data infrastructure, and supporting analytics to drive trading decisions. You will work with diverse datasets and modern tools to create, automate, and enhance processes that strengthen IET’s analytical and trading capabilities across energy markets (gas, oil, carbon, LNG). As part of a two-person data team, you will collaborate closely with our Data Engineer, sharing responsibilities for infrastructure and model development. This is an opportunity to shape the future of data-driven trading at INEOS.
RESPONSIBILITIES & ACCOUNTABILITIES
- Model Development: Create and maintain machine learning and AI models (initial focus on forecasting) using proper lifecycle management.
- Data Analysis: Provide detailed technical analysis of model outputs and methodologies.
- Collaboration: Work with the analytics team to enhance existing models and support trading insights.
- AI/ML Advancement: Drive forward AI and machine learning capabilities within IET.
- Infrastructure Support: Assist in maintaining and developing database infrastructure and related tooling.
- Methodology Review: Analyse and challenge modelling approaches, suggesting improvements.
- Visualization: Build and maintain dashboards for analytics and trading teams.
- Ad-hoc Analysis: Support trading desk and wider INEOS business with data-driven insights.
SKILLS, EXPERIENCE & EDUCATION
- University degree in a STEM subject (data-related discipline preferred).
- Strong proficiency in Python and SQL.
- Knowledge of statistical techniques, machine learning models, and validation methodologies.
- Experience with ML frameworks (e.g., PyTorch, scikit-learn).
- Familiarity with cloud platforms (Azure, AWS, Snowflake) preferred.
- Exposure to energy markets or trading environments is a plus.
BEHAVIOURAL SKILLS & PERSONAL ATTRIBUTES
- Excellent communication, adaptability, and ability to work both independently and collaboratively.
- Team player.
WHY JOIN US?
- Opportunity to work on impactful forecasting models and cutting-edge analytics.
- Dynamic role offering exposure to both data science and engineering.
- Small, agile team with significant influence on trading strategy.
- Career growth within a global business.
Please note this role is based onsite at our Knightsbridge office.
Data Scientist employer: INEOS Energy
Contact Detail:
INEOS Energy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. The more you engage, the better your chances of landing that Data Scientist role at INEOS.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models and data analysis projects. This will give potential employers a taste of what you can bring to the table, especially in forecasting and analytics.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your experience with ML frameworks and how you've tackled real-world data challenges. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our dynamic data team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your proficiency in Python, SQL, and any relevant machine learning frameworks. We want to see how you can contribute to our dynamic data team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and how it aligns with our mission at INEOS Energy Trading. Let us know why you're excited about the opportunity to work on forecasting models and analytics.
Showcase Relevant Projects: If you've worked on projects involving machine learning or data analysis, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they relate to energy markets or trading!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out on the chance to join our small, agile team!
How to prepare for a job interview at INEOS Energy
✨Know Your Models
Make sure you’re well-versed in the machine learning and AI models you’ve worked with. Be ready to discuss your approach to model development, including lifecycle management and validation methodologies. This will show that you understand the technical aspects and can contribute effectively to the team.
✨Brush Up on Python and SQL
Since strong proficiency in Python and SQL is crucial for this role, ensure you can demonstrate your skills during the interview. Prepare to solve coding problems or discuss past projects where you used these languages to manipulate data or build models.
✨Understand the Energy Market
Familiarise yourself with the basics of energy markets, especially gas, oil, and carbon trading. Being able to discuss how data science can impact trading decisions in these areas will set you apart and show your genuine interest in the role.
✨Show Your Collaborative Spirit
As part of a small data team, collaboration is key. Be prepared to share examples of how you’ve worked with others in the past, particularly in developing models or supporting analytics. Highlight your adaptability and communication skills to demonstrate you’re a great team player.
