Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist / ML Engineer

Xcede
Bath
6 months ago
Applications closed

Related Jobs

View all jobs

Consumer Lending Data Scientist

Consumer Lending Data Scientist

Data Scientist / Quant Engineer

Machine Learning Engineer (Databricks)

Data Scientist / Software Engineer

Senior Data Scientist/AI Engineer (Remote)

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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.