Junior Data scientist

About WPP Production

We are WPP Production - the unified global production company that brings together all of WPP's content producers, studios and craft experts into one connected organisation. We combine world-class human craft with next generation technology to originate, design, and deliver multi-channel content systems at scale. Built for borderless collaboration and powered by deep craft expertise, we are the production engine designed for today's always on, AI driven marketing world.

About WPP

WPP is the trusted growth partner for the world's leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com.

Role

We are seeking a Data Scientist with 2–4 years of experience who specializes in machine learning and deep learning techniques. The ideal candidate will design, train, and deploy advanced models to solve complex business problems, working with large-scale datasets and collaborating across engineering and product teams.

Key Responsibilities

Machine Learning & Deep Learning

• Develop, train, and optimize models using frameworks such as TensorFlow, PyTorch, or Keras.
• Apply deep learning architectures (CNNs, RNNs, Transformers) to tasks like image recognition, image segmentation,
• Ability to work with localisation and object detection algorithms like Yolo for advanced video analytics
• Experiment with large language models (LLMs) and fine-tune them for domain-specific applications. o Some exposure to AI Agents using frameworks like Langchain, Autogen etc
  
  

Data Analysis & Engineering

• Preprocess and manage structured and unstructured datasets.
• Implement feature engineering and dimensionality reduction techniques.
• Experience in cloud platforms like Azure, AWS or GCP is a big plus.
  
  

Deployment & Scalability

• Build end-to-end ML pipelines from data ingestion to model deployment.
• Collaborate with engineers to integrate models into production systems.
• Monitor model performance and retrain as needed.
  
  

Business Impact

• Translate business challenges into ML solutions.
• Present insights and recommendations to stakeholders using clear visualizations and reports.
  
  

Requirements

• Programming: Strong proficiency in Python (NumPy, Pandas, Scikit-learn) and ML/DL frameworks (TensorFlow, PyTorch, Keras).
• ML Expertise: Solid understanding of supervised/unsupervised learning, reinforcement learning, and neural networks.
• Deep Learning: Hands-on experience with CNNs, RNNs, LSTMs, and Transformer-based models.
• Data Handling: Strong SQL skills and familiarity with big data tools.
• Data Engineering: Experience in cloud platforms like Azure ML, Sagemaker, GCP etc
• Soft Skills: Strong analytical thinking, communication, and ability to work in cross-functional teams.
  
  

Why work here:

At WPP Production, you'll help shape the future of content production at a truly global scale. We bring together world-class talent, cutting-edge studios, and advanced technology to solve some of the most complex creative and production challenges in the industry. You'll work in a collaborative, borderless environment where craft excellence is valued, innovation is encouraged, and AI and next-generation tools are used to amplify not replace human creativity. With access to diverse projects, global career opportunities, and the backing of WPP's unmatched network, this is a place where you can grow your skills, make real impact, and create work that performs for every audience, across every channel, at every moment.

Inclusion and Impact

WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

Data

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