Corpay★3.0 (944)· London

You will work with Python, pandas, NumPy, scikit-learn, SQL, LLM/agentic AI/RAG systems, and cloud platforms (AWS, GCP, Azure). You will support the Data Science team in developing predictive models, machine learning workflows, and agentic LLM-based tools for Corpay’s commercial payments business.

This Data Scientist role uses Python, SQL, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Power BI, and Tableau for data analysis and machine learning. The position is at Information Tech Consultants, an IT management and consulting firm specializing in data science and IT solutions for UK and international clients.

WPP Media★4.0 (1)· London

This role uses Google Cloud Platform, Jira/Trello, and statistical methods to analyse media campaigns. You will work within WPP's Data, Tech, and Analytics team to deliver measurement frameworks, brand and conversion lift studies, and campaign effectiveness insights for the global client JLR.

Work with XGBoost, Random Forests, LSTM, transformers, LLMs, Python, R, SQL, Azure, Git, PowerBI, and Looker. You will drive business outcomes by applying AI/ML to solve problems in NLP, computer vision, and recommender systems for a global academic publisher.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

Sage★3.5 (901)· London

You will apply Python, R, SQL, XGBoost, Random Forests, LSTM, transformers, and Azure services to solve problems in NLP, computer vision, and recommender systems. The team builds AI/ML models to drive commercial impact for Sage, a global academic publisher of books, journals, and library resources.

You will use Python, R, SQL, Git-based platforms, Azure services, PowerBI, and Looker to build AI/ML solutions—including NLP, Computer Vision, recommender systems, and LLMs—for a global academic publisher of books, journals, and library resources.

Design and build an ML system for Advert Classification using MLOps, LLMs, Azure/AWS, and computer vision. Lead a team of Data Scientists through the ML lifecycle, experiment tracking, and production deployment. Provide technical direction and mentor engineers while shaping ML workflows.

You will lead a team of Machine Learning Engineers, using Python, SQL, GCP, Kubernetes, and KubeFlow alongside classical ML (e.g., XGBoost) and deep learning (e.g., BERT, LSTM) algorithms. The group develops ML/AI services for Kingfisher, a home improvement company owning B&Q, Screwfix, and other brands.

Elsevier★3.8 (769)· London

Work with Python, retrieval-augmented generation (RAG) pipelines, LangGraph, embeddings, re-ranking models, and platforms like Databricks. You will design and optimize lexical, vector, and hybrid search systems at scale, and define evaluation strategies for IR and GenAI across Elsevier's products.

Elsevier★3.8 (769)· London

You will work with Python, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, and Databricks. You will build and evaluate LLM-powered workflows, RAG pipelines, and retrieval systems for LeapSpace, Elsevier’s AI-powered research assistant.

JD.COM★3.8 (53)· London

Use Python, R, or Scala; ML frameworks (TensorFlow, PyTorch, Scikit‑learn); data‑viz tools (Tableau, Power BI); and big‑data platforms (Spark, Hadoop) with cloud ML pipelines (AWS Sagemaker, GCP Vertex AI, or Azure ML). You will build predictive models and analytics for personalization, recommendation, and customer segmentation on JD.com’s international e‑commerce operations.

Sainsbury’s★3.5 (16k)· London

Design and build ML systems for Advert Classification using modern ML tooling, LLMs, MLOps, and cloud platforms (Azure/AWS). You will lead a team of Data Scientists, driving the ML lifecycle, model evaluation, and production deployment.

You will work with Python, PyTorch, TensorFlow, MLOps, CI/CD, and cloud-based AI systems. You will lead the technical strategy for production ML systems that transform raw sports data and live video into real-time insights and personalised fan experiences. You will mentor engineers and data scientists while owning technical direction and delivery.

Tripledot Studios★2.8 (4)· London

Senior Machine Learning Engineer will work with ML techniques, CI/CD, Docker, Kubernetes, SQL, Python, MLFlow, Kubeflow, Trino, and AirFlow. The AI group implements ML algorithms for personalization across mobile game studios, directly improving retention, revenue, and player experience.

Jupiter Asset Management★4.3 (4)· London

Work with Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, Azure cloud tools, large language models (LLMs), and Power BI. As a Data Scientist at this investment management firm, you build predictive models, research alternative data sources for alpha signals, and deliver data-driven solutions directly with investment professionals.

McKinsey & Company★4.2 (952)· London

You will work with Python, pandas, numpy, scikit-learn, PyTorch/TF/Keras, LangChain, GitHub, and optional R/C++. You join McKinsey’s global Scientific AI team applying AI to therapeutics, chemicals, and materials (small molecules, proteins, mRNA) to build models and support client delivery.

Elsevier★3.8 (769)· London

You will work with Python, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, Databricks, and visualization tools. This role focuses on designing, building, and evaluating advanced AI for LeapSpace, Elsevier's AI-powered research assistant, and the broader Search & AI Platform to accelerate scientific discovery.

Elsevier★3.8 (769)· London

You’ll work with LLMs, generative AI, RAG, NLP, Python, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, and Databricks. The Platform Data Science team develops foundational AI for LeapSpace, Elsevier’s AI-powered research assistant, and the Search & AI Platform, helping researchers discover knowledge faster.

Amazon★3.5 (56k)· London

As an Applied Science Intern, you will work with machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, and formal methods, using Java, C++, or Python. You will design and develop end-to-end systems, working with Amazon scientists to create algorithms and models that are deployed into production.

Softwire, a UK digital consultancy, seeks a Senior Data Scientist with expertise in Python, PyTorch/TensorFlow/Keras, Scikit-learn, MLflow, and cloud platforms (Azure ML/SageMaker/Databricks) to design and deliver end-to-end data science projects across predictive analytics, computer vision, NLP, and MLOps for public and private sector clients. The role combines hands-on technical work with consultancy—scoping, designing and owning technical delivery with limited oversight—plus contributions to internal capability growth and methodology development, with no formal line management responsibilities.

Apple★4.1 (14k)· London

You'll work with Python (Streamlit, Flask, Django), SQL databases, cloud platforms (AWS, Azure, GCP), modern data warehouses (Snowflake, Dremio), ETL orchestration tools (Airflow, Metaflow), and data visualization libraries to build web applications and data pipelines. Apple's EMEIA Sales Finance team—approximately 150 employees across 4 regional hubs—needs you to design user-friendly financial analytics tools that help analysts make data-driven decisions and streamline reporting workflows.

JPMorgan★3.9 (20k)· London

You'll work with PyTorch, deep learning frameworks (transformers, CNNs, autoencoders), NLP techniques, Docker, cloud platforms (Azure/AWS/GCP), MLOps tools, and DAG-based pipelines to build scalable machine learning services for JPMorgan's Commercial & Investment Bank. The team develops AI-powered products that automate financial processes, enhance decision-making, and optimize business operations across the bank. This is an individual contributor role with optional management opportunities.

You'll work with Python, SQL, dbt, and Snowflake to build and maintain ETL/ELT pipelines for iwoca's analytics warehouse migration from a federated SQL system. The Core Systems team is transitioning to a data mesh operating model, requiring you to implement data testing frameworks, enable self-service analytics access, and establish governance practices across the organization. iwoca provides flexible financing to small businesses and has funded over 100,000 SMEs with more than £4 billion.