Hybrid: 3 days in the office / 2 days remote Location:London About RAPP We are RAPP – world leaders in activating growthwith precision and empathy at scale. As a global, next-generationprecision marketing agency we leverage data, creativity,technology, and empathy to foster client growth. We championindividuality in the marketing solutions we create, and in ourworkplace. We fight for solutions that adapt to the individual’sneeds, beliefs, behaviours, and aspirations. We foster an inclusiveworkplace that emphasizes personal well-being. Role Are you a datascientist eager to broaden your impact across the full stack ofdata science? Do you enjoy fast-paced environments, wearingmultiple 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-classmarketing agency. You’ll work alongside senior data scientists,engineers, strategists, and creatives to design, build, and deploymodels that make a real difference for global clients like RalphLauren, KFC, and Mercedes. This role is ideal for someone who’sready to grow quickly and thrives in a collaborative, high-velocitysetting. You’ll be part of a world-class team led by George Cushen(https://www.linkedin.com/in/cushen/), with deep experiencedelivering high-impact AI solutions across marketing and customerexperience. What You’ll Do - Model & Build: Support the designand deployment of pragmatic machine learning solutions — fromfeature engineering in SQL to model development in Python, anddeploying in production environments like AWS. - Explore &Prototype: Help bring new ideas to life by quickly prototyping newmodels and frameworks that solve business problems or spark clientinterest. - Own & Iterate: Take ownership of smallerworkstreams within larger projects, with opportunities to grow intoleading entire projects. - Solve Across the Stack: You’ll workend-to-end — writing clean, testable code, tuning models, workingwith 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 ofthought to everything you do. Pace and impact matter here. WhatYou’ll Bring Must-Have: - A degree in a STEM discipline (ComputerScience, Maths, Engineering, etc.) or equivalent practicalexperience. - 2–4 years of experience delivering DS/ML solutions inproduction environments — ideally in settings where you've had towear multiple hats (e.g., startups, small teams). - Fluency inPython and SQL; experience building and deploying modelsend-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 withoutgetting stuck in analysis paralysis. - Concise communication anddocumentation 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 andvalidation frameworks (e.g., A/B testing). - Startup or freelanceexperience that required pace, clarity, and autonomy. Why This Roleis Different Unlike many mid-level roles, this isn’t a one-trackposition. You won’t just tune models or clean data — you’ll do itall, with support from senior team members, but autonomy toexplore, experiment, and deliver. This is the perfect next step fora generalist with technical foundations and the hunger to grow intoa senior leader in a multi-disciplinary environment.#J-18808-Ljbffr
