At a Glance
- Tasks: Dive into data, design algorithms, and deliver insights that drive business decisions.
- Company: Innovative UK-based company using AI to analyse the open web.
- Benefits: Starting salary of £42,000–£45,000, flexible hybrid work model, and career growth.
- Other info: Collaborate closely with experts in a dynamic and supportive environment.
- Why this job: Join a world-class team and make a real impact in AI and data science.
- Qualifications: Degree in Maths, Computer Science, or 1-2 years in data science; programming skills required.
The predicted salary is between 42000 - 45000 € per year.
Join our mission to understand companies and sectors with Transparent AI. Are you a curious and ambitious Computer Science graduate or someone with 1-2 years of work experience looking to launch your career in AI and data science? Join our team of world-class data scientists and AI engineers, and help us build technology that understands written language at scale.
We’re a UK-based company using cutting-edge AI to analyse the open web and surface valuable insights on companies around the globe. We have developed proprietary AI for language understanding that reads the web and helps organisations research and track companies globally. As part of our team, you’ll work on innovative projects, tackle real-world data challenges, and collaborate closely with our CTO and team of data scientists.
This is a full-time role with a starting salary of £42,000–£45,000 and the opportunity to make a real impact from day one. We work in a flexible hybrid model, part remote and part from our central London (Clerkenwell) office.
What You'll Do
- Dive into raw data to assess quality, clean and structure it, and prepare it for downstream processing related to specific projects.
- Design and implement scalable, high-performance prediction algorithms.
- Collaborate with data scientists and software engineers to transform prototypes into robust, production-ready systems.
- Deliver insights that drive strategic business decisions and improvements.
Qualifications
- Bachelor's degree in Mathematics, Computer Science, Physics or Engineering.
- Alternatively, 1-2 years of experience in data science or data modelling.
- Deep understanding of machine learning (ML), clustering and classification techniques.
- Fluency in a programming language (Python, C, C++, Java, SQL).
- Familiarity with Big Data frameworks and visualisation tools (Cassandra, Hadoop, Spark, Tableau).
Data Scientist in London employer: Glass.AI
Join a forward-thinking company that champions innovation and collaboration in the heart of London. With a flexible hybrid work model, we offer a vibrant work culture that encourages personal growth and professional development, allowing you to make a meaningful impact from day one. Our commitment to cutting-edge AI technology not only empowers our employees but also positions us as leaders in the data science field, making us an excellent employer for those eager to advance their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with data science professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and data analysis. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and practical tests. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key, so let your passion for AI shine through!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are excited about joining our mission. Plus, it gives us a chance to see your enthusiasm right from the start!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight relevant skills, projects, and experiences that align with our mission at StudySmarter. We want to see how you can contribute to our innovative AI projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for AI and data science, and explain why you're excited about joining our team. Let us know how your background makes you a great fit for the role.
Showcase Your Projects:If you've worked on any data science projects, make sure to mention them! Whether it's a university project or something personal, we love seeing practical applications of your skills. It gives us insight into your problem-solving abilities.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. We can't wait to hear from you!
How to prepare for a job interview at Glass.AI
✨Know Your Data
Before the interview, brush up on your understanding of data cleaning and structuring. Be ready to discuss specific techniques you've used in past projects or during your studies. This will show your potential employer that you’re not just familiar with theory but can apply it practically.
✨Showcase Your Programming Skills
Make sure you can confidently talk about your experience with programming languages like Python or SQL. Prepare examples of how you've used these languages in real-world scenarios, especially in relation to machine learning or data modelling. This will demonstrate your technical prowess.
✨Understand the Company’s Mission
Research the company’s use of AI and how they analyse the open web. Being able to articulate how your skills align with their mission will set you apart. Think about how you can contribute to their projects and be ready to share your thoughts during the interview.
✨Prepare for Technical Questions
Expect questions on machine learning techniques, clustering, and classification. Review key concepts and be prepared to solve problems on the spot. Practising with mock interviews can help you feel more comfortable and confident when tackling these technical challenges.
