Data Scientist/ ML Engineer

Job Description Data Scientist/ ML Engineer – Data-Driven Digital Agency
Location:

Hybrid (London) or UK Remote

Are you a Data Scientist Or ML Engineer ready to make an impact across the full data science lifecycle? Do you thrive in fast-paced environments, enjoy wearing multiple hats, and take pride in turning ideas into production-ready solutions? My client is a leading data-driven digital agency, we are looking for a Data Scientist/ ML Engineer to join their high-impact Marketing Sciences team. You'll be working on cutting-edge data science projects that directly drive campaign performance, customer engagement, and revenue growth for some of the world's biggest brands.

What You’ll Be Doing:
Build & Optimise Models:

Design and implement predictive models including causal AI campaign modelling, forecasting engines, pricing elasticity models, and recommender systems.
Lead Projects & People:

Guide a team of data scientists across multiple projects. Depending on experience, this may include upskilling those around you.
Deliver Real Business Impact:

Use predictive and prescriptive analytics to generate insights that translate into tangible improvements for client campaigns and marketing strategy.
Prototype & Scale:

Develop tools, frameworks, and self-service prototypes that showcase the agency’s capabilities.
Client-Facing Influence:

Present technical concepts clearly to both technical and non-technical stakeholders.
Document & Collaborate:

Work cross-functionally and ensure processes are documented and scalable.
Must-Have Experience:
Extensive experience building machine learning models for marketing use cases ADVANCED skills in segmentation, recommendation, campaign optimisation, forecasting, etc.
Proficiency in Python, SQL, Bash, and Git. Familiarity with tools like Pandas, Jupyter notebooks, PyTorch.
Experience with advanced techniques including CausalAI, NLP, RNNs, GraphAI, GenAI, and Computer Vision.
Solid understanding of experimentation methods including A/B testing.
Strong communication skills and ability to translate complex analyses into actionable insights.
Nice-to-Haves:
Familiarity with marketing-specific measurement models such as Media Mix Modelling (MMM).
Knowledge of model versioning (e.g. MLFlow), API frameworks (FastAPI), or building dashboards (e.g. Dash or Streamlit).
The Opportunity:
You’ll work across multiple industries and household-name brands, contributing to meaningful campaigns powered by cutting-edge AI and analytics. This role offers variety, high visibility, and the opportunity to shape data strategy at both a technical and strategic level.

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