At a Glance
- Tasks: Support the development of predictive models and data-driven solutions for global brands.
- Company: Join RAPP, a leading precision marketing agency focused on growth through data and creativity.
- Benefits: Enjoy a hybrid work model with 3 days in the office and 2 days remote.
- Other info: This is a 6-month fixed-term contract ideal for early-career data enthusiasts.
- Why this job: Work on real projects, build models, and grow under expert mentorship in a collaborative environment.
- Qualifications: Solid foundation in statistics, programming skills in Python and SQL, and a growth mindset required.
The predicted salary is between 28800 - 43200 £ per year.
Rapp Collins 07 July 2025
Employment Type: Fixed Term Contract
Duration: 6 months
Hybrid: 3 days in the office / 2 days remote
Location: London
About RAPP
We are RAPP – world leaders in activating growth with precision and empathy at scale. As a global, next-generation precision marketing agency we leverage data, creativity, technology, and empathy to foster client growth. We champion individuality in the marketing solutions we create, and in our workplace. We fight for solutions that adapt to the individual’s needs, beliefs, behaviours, and aspirations. We foster an inclusive workplace that emphasizes personal well-being.
Role
Are you an aspiring data scientist with a strong foundation in statistical modelling, programming, and business problem-solving? Do you thrive on learning fast, solving real-world problems, and making an impact from day one? We’re looking for a Junior Machine Learning Engineer on a 6 months fixed term contract with a growth mindset and a solid grasp of data science fundamentals to join our world‑class team at RAPP. You’ll support senior team members in delivering machine learning and advanced analytics solutions for global brands like Ralph Lauren, KFC, and Mercedes. This role is perfect for someone at the start of their career who is passionate about applying their skills to commercial challenges and growing rapidly in a fast‑paced, collaborative environment. You’ll be joining a team led by George Cushen, known for delivering innovative AI solutions at scale across marketing and customer experience.
What You’ll Do
- Support the development of predictive models and data‑driven solutions that solve real marketing and customer problems.
- Conduct exploratory data analysis, feature engineering, and data cleaning to prepare data for modelling.
- Write clean, well‑documented Python and SQL code to support analysis and model development.
- Collaborate with other data scientists and analysts to turn insights into business recommendations.
- Communicate findings clearly to internal stakeholders – both technical and non‑technical.
- Learn quickly and continuously – from new tools and techniques to client domains and business challenges.
What You’ll Bring
Must‑Have:
- A strong foundation in statistics, probability, and machine learning fundamentals – either through a STEM degree, formal training, or self‑study.
- Fluency in Python and SQL, including experience with libraries like Pandas, Scikit‑learn or equivalent.
- Demonstrated ability to solve real‑world problems pragmatically using data.
- Clear, structured communication – especially the ability to explain complex topics simply.
- A growth mindset: curious, driven, humble, and eager to learn from others.
- Business acumen and commercial awareness – able to think critically about the impact of your work.
Nice‑to‑Have:
- Experience working on live projects in a business setting – e.g., internships, grad schemes, or startups.
- Familiarity with cloud tools (AWS, GCP, etc.) or version control (Git).
- Exposure to A/B testing, forecasting, causal AI, or graph AI.
- Experience working with marketing or customer‑level datasets.
Why This Role is Different
This is not your average junior role. You won’t be stuck doing just data cleaning or dashboards – you’ll work on real projects, build models, contribute ideas, and grow under the mentorship of a senior, highly experienced team. This is the perfect launchpad for someone who wants to accelerate their career in data science within a global creative agency.
How to Apply
Interested in this position? Please submit your resume and cover letter through the application portal.
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Junior Machine Learning Engineer (6 Months Fixed Term Contract) in London employer: Rapp Collins
At RAPP, we pride ourselves on being a leading precision marketing agency that values individuality and inclusivity in our workplace. As a Junior Machine Learning Engineer, you'll have the opportunity to work on impactful projects for renowned global brands while being supported by a collaborative team that fosters personal growth and continuous learning. Our hybrid work model in London allows for a balanced approach to work-life integration, making RAPP an excellent employer for those looking to kickstart their career in data science.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Machine Learning Engineer (6 Months Fixed Term Contract) in London
✨Tip Number 1
Familiarise yourself with RAPP's work and their approach to precision marketing. Understanding their projects and clients, like Ralph Lauren and KFC, will help you tailor your conversations during interviews and demonstrate your genuine interest in the role.
✨Tip Number 2
Brush up on your Python and SQL skills, especially with libraries like Pandas and Scikit-learn. Being able to discuss specific projects or challenges you've tackled using these tools will show your practical experience and readiness for the role.
✨Tip Number 3
Prepare to discuss your understanding of machine learning fundamentals and how they apply to real-world business problems. Think of examples where you've used data to drive decisions or solve issues, as this aligns perfectly with what RAPP is looking for.
✨Tip Number 4
Showcase your growth mindset by sharing experiences where you've learned from feedback or adapted to new challenges. RAPP values individuals who are eager to learn and grow, so highlighting this trait can set you apart from other candidates.
We think you need these skills to ace Junior Machine Learning Engineer (6 Months Fixed Term Contract) in London
Some tips for your application 🫡
Understand the Role:Before applying, make sure you fully understand the responsibilities and requirements of the Junior Machine Learning Engineer position. Familiarise yourself with the skills mentioned in the job description, such as proficiency in Python and SQL, and the importance of a growth mindset.
Tailor Your CV:Customise your CV to highlight relevant experiences and skills that align with the job description. Emphasise any projects or coursework related to machine learning, statistics, and programming, and ensure your communication skills are evident.
Craft a Compelling Cover Letter:Write a cover letter that showcases your passion for data science and your eagerness to learn. Mention specific examples of how you've applied your skills in real-world scenarios and express your enthusiasm for working with RAPP's innovative team.
Proofread Your Application:Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which is crucial in a technical role.
How to prepare for a job interview at Rapp Collins
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and SQL. Bring examples of projects where you've used libraries like Pandas or Scikit-learn, and be ready to explain your thought process in solving real-world problems.
✨Demonstrate Your Growth Mindset
RAPP values a growth mindset, so share experiences that highlight your curiosity and eagerness to learn. Discuss how you've adapted to new tools or techniques in the past and how you approach challenges with a positive attitude.
✨Communicate Clearly
Practice explaining complex topics in simple terms. Since you'll need to communicate findings to both technical and non-technical stakeholders, clarity in your communication will be key during the interview.
✨Prepare for Real-World Applications
Think about how your skills can address marketing and customer challenges. Be ready to discuss how you would approach developing predictive models or conducting exploratory data analysis in a business context.
