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- Tasks: Join BP as an Apprentice Data Scientist, working on real data and ML projects.
- Company: BP, a leading energy company with a focus on digital transformation.
- Benefits: Starting salary of £22,100, £3,000 sign-on bonus, and flexible benefits.
- Why this job: Kickstart your career in data science with hands-on experience and professional development.
- Qualifications: Aged 18+, A-levels or Level 3 qualification, and coding skills required.
- Other info: Remote or hybrid work options available, with excellent growth opportunities.
The predicted salary is between 8000 - 10000 £ per month.
We are working with BP on this opportunity! Apprenticeship – Digital (Data Science and Machine Learning) BP Energy – Sunbury-on-Thames • Remote or Hybrid £22,100 + £3,000 sign-on bonus.
BP is hiring Level 4 Data Science and Machine Learning Apprentices to join its digital organisation. Over this two-year programme, you’ll work on real data and ML projects alongside engineers, analysts, and product teams while completing a Level 4 qualification (likely delivered by Corndel). This programme is ideal for school or college leavers, or individuals without a university degree looking to start a career in data and digital.
What you’ll do:
- Work in cross-disciplinary teams with data scientists, data engineers, software engineers, and business partners.
- Build scalable, reusable data science products using statistical and machine learning techniques.
- Perform data analysis to generate actionable insights.
- Learn best practices across design, code reviews, testing, monitoring, and documentation.
- Contribute to real projects across BP’s digital transformation initiatives.
- Receive structured professional development through the Elevate programme.
What you’ll need:
- Aged 18+ by September 2026.
- Completing A-levels or further education in 2026, or holding a relevant Level 3 qualification.
- Demonstrable coding ability (assessed during the process).
- A-level grade C or above in Computer Science/IT, Maths, or Physics.
- GCSEs (A*–C / 9–4) in English and Maths.
- Eligible under apprenticeship levy rules (e.g., UK/EEA residency for 3+ years, no higher-level qualification).
- Must not already hold a university degree.
Location: BP Sunbury – International Centre for Business and Technology (ICBT), Chertsey Road, Sunbury-on-Thames.
Programme start date: 7 September 2026.
Rewards and benefits:
- £22,100 starting salary
- £3,000 sign-on bonus
- Wellbeing allowance up to £1,500 per year
- Flexible benefits allowance (20 percent of salary)
- Private medical insurance
- Annual discretionary bonus
- BP share plans
- Hybrid working and early-career support
Apply now via Haystack.
Apprentice Data Scientist in Manchester employer: Haystack
Contact Detail:
Haystack Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Apprentice Data Scientist in Manchester
✨Tip Number 1
Network like a pro! Reach out to current or former apprentices at BP, or even data science professionals on LinkedIn. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Prepare for the coding assessment! Brush up on your coding skills and practice common data science problems. We’ve got resources that can help you get ready, so don’t skip this step!
✨Tip Number 3
Show your passion for data! During interviews, share any personal projects or experiences related to data science. It’s all about demonstrating your enthusiasm and commitment to learning.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re here to support you every step of the way, so don’t hesitate to reach out if you have questions!
We think you need these skills to ace Apprentice Data Scientist in Manchester
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let us see your enthusiasm for data science and machine learning. Share any relevant projects or experiences that highlight your interest in the field. We love to see candidates who are genuinely excited about what they could bring to the team!
Tailor Your Application: Make sure to customise your application to fit the role. Highlight your coding skills and any relevant qualifications, like your A-levels or Level 3 qualifications. We want to know how your background aligns with what we're looking for at BP!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language and avoid jargon where possible. We appreciate a well-structured application that makes it easy for us to see your strengths and potential.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need about the apprenticeship programme there. We can’t wait to see what you’ve got!
How to prepare for a job interview at Haystack
✨Know Your Data Science Basics
Make sure you brush up on your data science fundamentals before the interview. Understand key concepts like machine learning algorithms, data analysis techniques, and coding languages relevant to the role. This will not only help you answer technical questions but also show your enthusiasm for the field.
✨Showcase Your Projects
If you've worked on any data-related projects, whether in school or on your own, be ready to discuss them. Highlight what you did, the challenges you faced, and the outcomes. This demonstrates your practical experience and problem-solving skills, which are crucial for the role.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare thoughtful questions about the apprenticeship programme, team dynamics, or specific projects at BP. This shows your genuine interest in the position and helps you assess if it's the right fit for you.
✨Practice Coding Challenges
Since coding ability is assessed during the process, practice common coding challenges that might come up in the interview. Websites like LeetCode or HackerRank can be great resources. Being comfortable with coding under pressure will boost your confidence and performance.
