Avatar for RAPP
We stand up for individuality
  • B2B
  • Scale Stage
    Rapidly increasing operations

Junior Machine Learning Engineer (6 Months Fixed Term Contract)

Posted: 1 year ago
Job Location
Visa Sponsorship

Not Available

RelocationAllowed

About the job

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 (https://www.linkedin.com/in/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

About the company

RAPP company logo
We stand up for individuality5000+ Employees
  • B2B
  • Scale Stage
    Rapidly increasing operations
Learn more about RAPP image

Founders

Ashley Alvarado
Founder
New York City
image
View the team image

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