Data Scientist - Ad Campaign Performance

London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist Placement

Data Scientist (NLP & LLM Specialist)

Data Scientist - Renewable Energy

Data Scientist - Supply Chain Optimisation

Experienced Data Scientist
12 month contract TBC
Market Rate - Depending on experience level
IR35 Status Outside TBC
Hybrid/Remote (UK Right to work) with Travel to London

Experienced Data Scientist working on a new initiative to build and deploy a modelling solution to predict & optimise advertising campaign performance as part of a productionised, customer-facing SaaS product. Ideally looking for experience in Media/Advertising sector or similar.

Experience - Must-haves:

  • Must have a number of years working commercially as a Data Scientist
  • Solid understanding of & real-world experience implementing data science & statistical principles - e.g. applied statistics, model selection, cross-validation, objective functions, hyperparameter tuning, continuous & discrete optimisation problems, etc.
  • Strong interpersonal skills & ability to explain data science principles with clarity to non-technical stakeholders when required
  • Extensive knowledge of Python programming principles including object-oriented programming, performance optimisation
  • Experience developing & deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable)
  • Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc.
  • Strong knowledge of SQL and its use for data preparation & feature engineering
  • Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies
  • Some knowledge of containerisation & use of tools like Docker & Docker Compose

    Nice-to-haves (Mix of the following but not all essential):
  • Experience working with Google Cloud products for ML including Vertex AI Pipelines & BigQuery
  • Experience with dbt (data build tool)
  • Previous experience working with advertising data
  • Experience with FastAPI or other Python API frameworks
  • Experience with dashboarding tools such as Looker Studio, Tableau or PowerBI
  • Experience working on a SaaS (Software-as-a-Service) application
  • Experience working with Kubeflow Pipelines
  • Experience developing on a Mac / Unix environment
  • Knowledge of CICD pipeline design & implementation
  • Experience modelling using GenAI, LLMs or neural networks in general
  • A/B testing experience / Statistical hypothesis testing experience

    Everybody is welcome
    Diversity and Inclusion Statement. | PCR Digital
    "At PCR Digital, we are committed to ensuring that diversity, equity and inclusion play a role at all stages of our recruitment - it is important to us that our own company culture and the culture of our network is as varied and supportive as possible. We love people (it's why we do what we do), so, regardless of background, we welcome you to work with us or apply to any of our jobs if you feel that they are right for you

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.

How Many Robotics Tools Do You Need to Know to Get a Robotics Job?

If you’re pursuing a career in robotics, it can feel like the list of tools you should learn never ends. One job advert asks for ROS, another mentions Gazebo, another wants experience with Python, Linux, C++, RobotStudio, MATLAB/Simulink, perception stacks, control frameworks, real-time OS, vision libraries — and that’s just scratching the surface. With so many frameworks, languages and platforms, it’s no wonder robotics job seekers feel overwhelmed. But here’s the honest truth most recruiters won’t say explicitly: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real robotics problems reliably and explain your reasoning clearly. Tools matter — but only in service of outcomes. So the real question isn’t how many tools you should know, but which tools you should master and why. For most robotics roles, the answer is significantly fewer — and far more focused — than you might assume. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable, confident, and ready to contribute from day one.

What Hiring Managers Look for First in Robotics Job Applications (UK Guide)

Robotics is one of the most dynamic, interdisciplinary fields in technology — blending mechanical systems, embedded software, controls, perception (AI/vision), modelling, simulation and systems integration. Hiring managers in this space are highly selective because robotics teams need people who can solve real-world problems under constraints, work across disciplines, and deliver safe, reliable systems. And here’s the reality: hiring managers do not read every word of your CV. Like in many tech domains, they scan quickly — often forming a judgement in the first 10–20 seconds. In robotics, those first signals are especially important because the work is complex and there’s a wide range of candidate backgrounds. This guide unpacks exactly what hiring managers look for first in robotics applications and how to optimise your CV, portfolio and cover letter so you stand out in the UK market.

The Skills Gap in Robotics Jobs: What Universities Aren’t Teaching

Robotics is no longer confined to science fiction or isolated research labs. Today, robots perform critical tasks across manufacturing, healthcare, logistics, agriculture, defence, hospitality and even education. In the UK, businesses are embracing automation to improve productivity, reduce costs and tackle labour shortages. Yet despite strong interest and a growing number of university programmes in robotics, many employers report a persistent problem: graduates are not job-ready for real-world robotics roles. This is not a question of intelligence or dedication. It is a widening skills gap between what universities teach and what employers actually need in robotics jobs. In this article, we’ll explore that gap in depth — what universities do well, where their programmes often fall short, why the disconnect exists, what employers really want, and how you can bridge the divide to build a thriving career in robotics.