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- Tasks: Design and deploy data science solutions in a fast-paced energy trading environment.
- Company: Join a leading Oil and Gas Major with a focus on innovation.
- Benefits: Competitive daily rate, guaranteed 6-month contract, potential for extension.
- Why this job: Make a real impact in energy trading while working with cutting-edge technology.
- Qualifications: Strong Python skills, experience in machine learning, and excellent communication abilities.
- Other info: Immediate start in January; apply now to secure your interview!
The predicted salary is between 48000 - 72000 £ per year.
We’re hiring multiple Senior Data Scientists to join a high-impact energy trading environment for an Oil and Gas Major. This role is focused on designing, building, and deploying robust data science and machine learning solutions that directly support trading and commercial decision-making. It’s a hands-on position suited to experienced practitioners who are comfortable operating in complex, fast-paced environments.
What you will do …
- Building and deploying scalable data science and machine learning solutions into production
- Working closely with data engineers, software engineers, and business stakeholders across trading functions
- Applying strong statistical and machine learning foundations to solve real-world trading and optimisation problems
- Performing deep-in-depth data analysis to deliver clear, actionable insights
- Owning the full data science lifecycle, from initial exploration and prototyping through to deployment and ongoing support
- Contributing to GenAI / LLM-driven use cases and clearly articulating outcomes to technical and non-technical audiences
- Writing clean, maintainable, and well-documented code within complex enterprise systems
- Taking part in technical reviews and discussions, with a strong focus on value delivery and pragmatism
What I need from you …
- Strong hands-on development experience in Python and/or other object-oriented languages such as Java
- Excellent grounding in statistics, machine learning, and core mathematical concepts
- Exposure to modern data science tooling, including LLMs and RAG-style approaches
- Advanced SQL skills
- Experience working at enterprise scale, ideally in trading or similarly data-intensive domains
- Strong written and verbal communication skills
- Comfortable with technical interview formats, including live coding, OOP design, and SQL challenges
This role requires urgent attention as my client ideally needs people to start in January. Successful applicants will progress to interview ASAP to make this start date possible. Should you be interested please do not hesitate to apply now.
Lead Data Scientist - Energy employer: Paritas Recruitment
Contact Detail:
Paritas Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Energy
✨Tip Number 1
Network like a pro! Reach out to your connections in the energy sector and let them know you're on the hunt for a Lead Data Scientist role. Personal recommendations can make all the difference, so don’t be shy about asking for introductions.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your Python skills and get comfortable with live coding challenges. Practising common data science problems will help you feel more confident when it’s time to showcase your expertise.
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, having tangible examples of your work in machine learning and data analysis can really impress potential employers. Make sure to highlight any relevant experience in trading or optimisation.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Lead Data Scientist - Energy
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience in Python, machine learning, and any relevant projects in the energy sector. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science in the energy sector and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's building scalable solutions or performing deep data analysis, we want to see your hands-on experience. Include links to your GitHub or portfolio if you have them.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Paritas Recruitment
✨Know Your Data Science Fundamentals
Brush up on your statistics and machine learning concepts. Be ready to discuss how you've applied these in real-world scenarios, especially in trading or optimisation problems. This will show that you can not only understand the theory but also implement it effectively.
✨Showcase Your Coding Skills
Prepare for live coding challenges by practising Python and SQL. Make sure you can write clean, maintainable code under pressure. Familiarise yourself with object-oriented programming principles, as you'll likely need to demonstrate these during the interview.
✨Communicate Clearly
You’ll need to articulate complex ideas to both technical and non-technical audiences. Practice explaining your past projects and the impact they had on decision-making. Clear communication is key, especially when discussing your contributions to GenAI or LLM-driven use cases.
✨Understand the Energy Sector
Research the current trends and challenges in the energy trading market. Being knowledgeable about the industry will help you connect your skills to the role and demonstrate your genuine interest in the position. It’s all about showing that you’re not just a data scientist, but one who understands the business context.