Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a talented team to develop cutting-edge AI using machine learning techniques.
- Company: Be part of a fast-growing, innovative company revolutionising its industry.
- Benefits: Enjoy free meals, snacks, team events, and generous annual leave.
- Why this job: Work on exciting projects with top technologists in a vibrant office environment.
- Qualifications: 2+ years in Data Science, solid Python skills, and some Java experience required.
- Other info: Hybrid work model: 3 days in the office, overlooking Notting Hill.
The predicted salary is between 46000 - 64000 £ per year.
You will be joining a fast-growing, research-driven company building an artificial intelligence using novel machine learning techniques. My client is revolutionising their industry with a track record of building things that others have ruled out as impossible. The Data Scientist will join a very bright, talented team of engineers with the guidance of technologists who have helped build some of the best-known technology companies today. You will work closely with senior engineers and data scientists to quickly learn and apply machine learning techniques to real-world problems, shipping results fast. The role will be very interesting and diverse and will involve keeping ahead of the latest technologies.
Core skills for the Data Scientist:
- 2yrs+ in a commercial Data Science / Machine Learning role
- Solid experience of Python and some Java (Could be from University projects)
- A strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
- Familiarity with cloud platforms (AWS) and Kubernetes for deploying
- A degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience in engineering.
Salary for the Data Scientist / Machine Learning Engineer will depend on experience, but expect between £55,000 and £80,000 + Pension + benefits.
Other benefits include:
- Free breakfast/Lunch and coffee, drinks and snacks all day/every day.
- Regular team events (dinner, bowling, karting, poker nights, board-games etc.)
- The latest tech, generous annual leave and an amazing office with a balcony overlooking Notting Hill.
Applicants must have the right to work in the UK, no sponsorship is offered for this role.
Data Scientist (, , United Kingdom) employer: Bentley Whitaker Search and Selection
Contact Detail:
Bentley Whitaker Search and Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (, , United Kingdom)
✨Tip Number 1
Make sure to showcase your hands-on experience with Python and Java during any networking opportunities. Engage in conversations about your projects or contributions to open-source initiatives that highlight your coding skills.
✨Tip Number 2
Stay updated on the latest machine learning frameworks like TensorFlow and PyTorch. Join relevant online communities or forums where you can discuss these technologies, as this will help you demonstrate your passion and knowledge during interviews.
✨Tip Number 3
Consider attending meetups or workshops focused on AI and machine learning. This not only expands your network but also gives you a chance to learn from industry experts, which can be a great talking point when you apply.
✨Tip Number 4
Familiarise yourself with AWS and Kubernetes, as these are essential for deploying machine learning models. You could even set up a small project to demonstrate your ability to use these tools effectively, which will impress potential employers.
We think you need these skills to ace Data Scientist (, , United Kingdom)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and Java, as well as your familiarity with machine learning frameworks like scikit-learn, TensorFlow, and PyTorch. Use specific examples from your previous roles or projects to demonstrate your skills.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background in data science aligns with their mission of revolutionising the industry through AI. Be sure to include any relevant projects or experiences that showcase your ability to apply machine learning techniques.
Showcase Relevant Projects: If you have worked on any projects involving machine learning or AI, be sure to include them in your application. Describe your role, the technologies used, and the outcomes achieved. This will help demonstrate your practical experience and problem-solving abilities.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops you've completed related to data science or machine learning. This shows your commitment to staying updated with the latest technologies and trends in the field, which is crucial for this role.
How to prepare for a job interview at Bentley Whitaker Search and Selection
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python and any exposure to Java during the interview. Be prepared to discuss specific projects where you've used scikit-learn, TensorFlow, or PyTorch, as this will demonstrate your hands-on knowledge of machine learning frameworks.
✨Understand the Company’s Vision
Research the company’s mission and recent projects. Understanding how they are revolutionising their industry with AI will allow you to align your answers with their goals and show that you're genuinely interested in being part of their innovative team.
✨Prepare for Technical Questions
Expect to face technical questions related to machine learning algorithms and cloud platforms like AWS. Brush up on your knowledge of core ML concepts and be ready to explain how you would apply them to real-world problems, as this is crucial for the role.
✨Demonstrate Team Collaboration
Since the role involves working closely with senior engineers and data scientists, be ready to discuss your experiences in collaborative environments. Share examples of how you’ve successfully worked in teams, tackled challenges together, and contributed to achieving common goals.
