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 a data
scientist eager to broaden your impact across the full stack of
data science? Do you enjoy fast-paced environments, wearing
multiple hats, and turning ideas into production-ready solutions?
At RAPP, we’re looking for a Data Scientist with a growth mindset,
a generalist toolkit, and an appetite to grow within a world-class
marketing agency. You’ll work alongside senior data scientists,
engineers, strategists, and creatives to design, build, and deploy
models that make a real difference for global clients like Ralph
Lauren, KFC, and Mercedes. This role is ideal for someone who’s
ready to grow quickly and thrives in a collaborative, high-velocity
setting. You’ll be part of a world-class team led by George Cushen
(https://www.linkedin.com/in/cushen/), with deep experience
delivering high-impact AI solutions across marketing and customer
experience. What You’ll Do - Model & Build: Support the design
and deployment of pragmatic machine learning solutions — from
feature engineering in SQL to model development in Python, and
deploying in production environments like AWS. - Explore &
Prototype: Help bring new ideas to life by quickly prototyping new
models and frameworks that solve business problems or spark client
interest. - Own & Iterate: Take ownership of smaller
workstreams within larger projects, with opportunities to grow into
leading entire projects. - Solve Across the Stack: You’ll work
end-to-end — writing clean, testable code, tuning models, working
with APIs, and understanding data pipelines and infrastructure. -
Communicate Simply: Share findings and rationale in a clear,
concise way, tailored to technical and non-technical audiences. -
Learn Fast, Move Fast: Bring energy, curiosity, and clarity of
thought to everything you do. Pace and impact matter here. What
You’ll Bring Must-Have: - A degree in a STEM discipline (Computer
Science, Maths, Engineering, etc.) or equivalent practical
experience. - 2–4 years of experience delivering DS/ML solutions in
production environments — ideally in settings where you've had to
wear multiple hats (e.g., startups, small teams). - Fluency in
Python and SQL; experience building and deploying models
end-to-end, from feature engineering to performance validation. -
Comfort with cloud tools (AWS preferred), Git, and CI/CD pipelines.
- Ability to work independently and juggle priorities without
getting stuck in analysis paralysis. - Concise communication and
documentation skills, especially under time pressure. Nice-to-Have:
- Experience with marketing data or customer-level modelling (e.g.,
uplift, attribution, causal AI, graph AI, campaign optimization,
spend optimization). - Exposure to MLOps tools like MLflow,
FastAPI, Airflow, or similar. - Experience with experimentation and
validation frameworks (e.g., A/B testing). - Startup or freelance
experience that required pace, clarity, and autonomy. Why This Role
is Different Unlike many mid-level roles, this isn’t a one-track
position. You won’t just tune models or clean data — you’ll do it
all, with support from senior team members, but autonomy to
explore, experiment, and deliver. This is the perfect next step for
a generalist with technical foundations and the hunger to grow into
a senior leader in a multi-disciplinary environment.
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