Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and build machine learning models to tackle real-world challenges.
- Company: Join a fast-growing team at the forefront of data science and AI.
- Benefits: Enjoy a competitive salary, hybrid working, and additional perks like private healthcare.
- Why this job: Make a meaningful impact while collaborating with experts in a supportive culture.
- Qualifications: Must have a Masterâs degree in a relevant field and strong Python skills.
- Other info: This role is ideal for recent graduates eager to apply their knowledge.
The predicted salary is between 28000 - 36000 ÂŁ per year.
Junior AI Data Scientist â Masterâs Graduate Role (High-Impact, Product-Focused)
Location: London (Hybrid)
Start Date: ASAP
The opportunity
If youâre a top Masterâs grad who wants to work on real production problems (not endless dashboards), this is a chance to join a high-performing group delivering machine learning and applied AI into live environments.
Youâll work on projects like prediction, optimisation, anomaly detection, and intelligent automationâowning meaningful pieces of the pipeline and seeing your work drive outcomes.
Expect high standards, strong mentorship, and the space to move quickly.
What youâll work on
- Build and improve ML/AI models that solve measurable business problems
- Run experiments, quantify impact, and iterate fast (including A/B testing where appropriate)
- Partner with engineering and product to design scalable, reliable solutions
- Communicate clearly: turning complex modelling into decisions stakeholders can act on
- Contribute to internal R&D: new approaches, paper-to-production exploration, model performance reviews
What makes this role different
- Production mindset: youâll learn how to deliver models that are monitored, reliable, and used
- High-calibre environment: collaborative, ambitious team with strong technical bar
- Ownership early: youâll ship real work within weeks, not months
- Growth runway: mentorship, code reviews, clear progression, and exposure to modern ML tooling
What weâre looking for
- A recently completed Masterâs degree (Russell Group preferred) in Data Science, Computer Science, Mathematics, Physics, Engineering, or similar
- Excellent Python skills and ML foundations (e.g. pandas, NumPy, scikit-learn; strong coding practices matter)
- Strong grasp of model evaluation, statistics, and experimentation
- Confident working with data at scale using SQL (and a practical approach to messy data)
- Curiosity, speed, and pride in qualityâsomeone who enjoys digging into hard problems
- Strong communication skills and willingness to collaborate across teams
- Full right to work in the UK (no visa sponsorship available)
Nice to have (not required)
- Deep learning exposure (PyTorch / TensorFlow)
- Cloud experience (AWS/GCP/Azure)
- Familiarity with MLOps concepts (monitoring, CI/CD, Git, Docker)
- Experience with NLP, time series, recommender systems, or optimisation
đĄ Hybrid working (London)
đ Mentorship + progression: structured development, training budget, regular feedback
đ Modern stack: current ML tooling, good engineering practices, and time to do things properly
How to apply
Send your most up-to-date CV and weâll arrange an initial call ASAP.
#J-18808-Ljbffr
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Junior Data Scientist
â¨Tip Number 1
Network with professionals in the data science field, especially those who work at StudySmarter or similar companies. Attend industry meetups, webinars, or conferences to make connections and learn more about the role.
â¨Tip Number 2
Showcase your projects on platforms like GitHub or personal websites. Highlight any machine learning models or data analysis projects you've completed during your Master's, as this will demonstrate your practical skills and passion for the field.
â¨Tip Number 3
Prepare to discuss your understanding of machine learning concepts and your experience with Python and SQL during interviews. Be ready to explain how you've applied these skills in real-world scenarios or academic projects.
â¨Tip Number 4
Stay updated on the latest trends in data science and AI. Being knowledgeable about recent advancements can help you engage in meaningful discussions during interviews and show your enthusiasm for continuous learning.
We think you need these skills to ace Junior Data Scientist
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that align with the Junior Data Scientist role. Emphasise your programming skills in Python, any projects involving machine learning, and your academic achievements.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your eagerness to solve real-world problems. Mention specific projects or experiences that demonstrate your understanding of machine learning concepts and your ability to collaborate effectively.
Highlight Relevant Coursework: In your application, include any relevant coursework from your Masterâs degree that pertains to data science, machine learning, or statistics. This will help demonstrate your academic foundation and readiness for the role.
Showcase Communication Skills: Since the role involves presenting findings to both technical and non-technical stakeholders, provide examples in your application of how you've effectively communicated complex ideas in the past, whether through presentations, reports, or collaborative projects.
How to prepare for a job interview at Intellect Group
â¨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python and any experience you have with libraries like NumPy, pandas, and scikit-learn. Bring examples of projects or coursework where you've applied these skills, as this will demonstrate your practical knowledge.
â¨Understand the Role's Requirements
Familiarise yourself with the core responsibilities of a Junior Data Scientist. Be ready to explain how your academic background and any relevant experience align with tasks such as data cleaning, model building, and presenting findings to stakeholders.
â¨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Practice explaining your thought process when tackling complex datasets or designing machine learning models, as this will highlight your analytical skills and creativity.
â¨Demonstrate Your Passion for Learning
Convey your enthusiasm for staying current with advancements in data science and AI. Share any recent articles, courses, or projects that showcase your commitment to continuous learning and how you plan to contribute new ideas to the team.
