At a Glance
- Tasks: Apply advanced machine learning techniques in real-world commercial settings.
- Company: Join a leading data science programme in the heart of London.
- Benefits: Earn the London Living Wage, receive expert training, and access a vast alumni network.
- Other info: Intensive eight-week programme with a focus on innovation and real impact.
- Why this job: Kickstart your AI career with hands-on experience and mentorship from industry experts.
- Qualifications: STEM degree and a solid foundation in data science required.
The predicted salary is between 30000 - 40000 £ per year.
Faculty is offering a Fellowship in data science based in London. This intensive eight-week program focuses on applying advanced machine learning techniques in high-stakes commercial environments, preparing you for a career in AI.
As a Fellow, you will receive expert-led training and mentorship, earn the London Living Wage, and gain access to a community of 500+ alumni.
The program seeks candidates with a STEM degree, strong data science foundation, and a passion for innovation.
Data Science Fellowship: Real-World ML in London (Paid) employer: Faculty
Faculty is an exceptional employer that fosters a vibrant work culture centred around innovation and collaboration in the heart of London. As a Fellow, you will benefit from expert mentorship, earn a competitive wage, and join a thriving community of over 500 alumni, all while gaining invaluable experience in real-world machine learning applications. This programme not only equips you with advanced skills but also opens doors for future career opportunities in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Fellowship: Real-World ML in London (Paid)
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Data Science Fellowship: Real-World ML in London (Paid)
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Faculty will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Faculty
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Faculty.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Faculty that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
