Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

Kingfisher★3.8 (77)· London

Senior Implementation Analyst at Kingfisher, working with GA360, GA4, Google Tag Manager, Tealium iQ, JavaScript, Tealium EventStream, Google Marketing Platform, and Google Cloud. You will design and implement tagging and measurement strategies for digital platforms, partner with Product, Data, and Analytics teams to drive optimisation, and manage tracking across websites and mobile apps.

Data Idols★0.0· London

You will use Python, machine learning, recommender systems, LLMs, Generative AI, conversational

Amazon★3.5 (56k)· London

Develop generative AI and large models using Java, C++, Python, and Unix/Linux for Prime Video’s observability team, which combines log management, tracing, and AI-powered analytics to detect and diagnose issues at unprecedented speed.

You will work with Microsoft Fabric, Power BI, SQL, DAX, and AI-enabled tools to build ELT/ETL pipelines and semantic models. The role shapes a modern analytics platform for a global private markets investment firm, delivering trusted data products to support investment and business teams.

Bloomberg★3.8 (1.1k)· London

You'll work with Python, SQL, and modern AI-assisted tools to own the data management strategy and roadmap for Bloomberg's environmental regulatory data products, including EU Taxonomy, SFDR, and CSRD. You'll partner with Engineering and Product to evolve data models, quality frameworks, and operational controls that ensure scalable, auditable data products.

Mastercard★4.0 (846)· London

You will work with LLMs, GenAI, Agentic AI, PowerBI, Qlik Sense, Tableau, AWS, Databricks, and Microsoft Azure, with Python and SQL preferred. Within Vocalink’s Data & Insights function, you will deliver data-led and AI-driven solutions for UK payment reporting and customized analytics.

BBC★4.2 (835)· London

Develop statistical and machine learning models using Python or R and SQL on a data and machine learning platform to understand audience behaviour. You will work with the 12-person Data Science team on audience measurement, forecasting, and applied ML for BBC digital products like iPlayer and News.

You'll work with Trino, Iceberg, dbt, Airflow, Kafka, Python, SQL, Java or Scala to build and optimize data pipelines on a Lakehouse following Medallion Architecture (Bronze, Silver, Gold layers). You'll join Wise’s Data Onboarding Team, part of the Finance Squad that stewards the company’s financial truth by processing hundreds of millions of high-throughput financial events daily into audit-ready structures. The team abstracts product complexity into reusable, domain-agnostic stream-enrichment pipelines.

Design, build, and deploy GenAI and ML solutions using OpenAI APIs, RAG, Python, Databricks, Spark, Delta Lake, and AWS (S3, Redshift, Lambda). You will work on predictive models and enterprise GenAI apps for Product, Sales, Finance, Marketing, Customer Success, and Engineering, owning projects end-to-end and integrating with Salesforce and Oracle platforms.

Design, build, and deploy quantitative models using Python, R, and libraries (numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot) plus NLP tools, SQL, AWS, Sagemaker, DataBricks, Snowflake, MLFlow, and Weights & Biases. The team creates systematic country risk analytics and ML/NLP pipelines for BMI’s market insights, supporting clients in risk assessment.

Work with Python, Pandas, NumPy, Scikit-learn, SQL, LLMs, RAG, and MLOps to design, build, and deploy enterprise-scale AI/ML solutions improving operational efficiency, service resilience, and customer outcomes at LSEG, a global financial markets infrastructure and data business.

You will use SQL, Python or R to build statistical and machine learning models on the BBC’s data platform. You will join a team of around 12 Data Scientists analysing audience behaviour, improving audience measurement and supporting strategic decisions across BBC digital products like iPlayer and Sounds.

Senior Software Engineer II building data pipelines on Trino, Iceberg, Kafka, dbt, Airflow, and Python/SQL for a Finance Squad. The team handles high-throughput financial event data within a Medallion Architecture, creating reusable stream-enrichment pipelines to support financial reporting and assurance at a global money-transfer company.

You will work with Python, modern ML frameworks, deep learning, LLMs, RAG, Agentic AI, and Multimodal AI. You will join a newly formed research team at a major UK organisation, exploring next-generation Generative AI and defining technical direction for large-scale customer-facing AI products, turning research into production systems.

King is collecting profiles for future AI/ML, Data Science, and Analytics roles. Work may involve Python, SQL, Spark, PyTorch, TensorFlow, scikit-learn, cloud platforms and ML pipelines, supporting mobile games like Candy Crush Saga played by over 200 million monthly active users.

Design, develop, and evaluate machine learning models using Python, PyTorch, TensorFlow, statistical modelling, deep learning, and multimodal AI for the ASOS AI Demand Forecasting platform. This platform provides demand forecasts to power replenishment, AI-powered pricing, and supply chain optimisation. You will also mentor other scientists and provide technical leadership on complex modelling projects.

Wise★3.5 (42)· London

Work with Trino, Iceberg, Kafka, dbt, Airflow, Python, SQL and Java/Scala to build streaming data pipelines on a Lakehouse using Medallion Architecture (Bronze/Silver/Gold). You will own data extraction, cleaning and modeling for the Data Onboarding team, which bridges product events and audit-ready financial structures for Wise’s global cross-border money movement platform.

LSEG★3.7 (402)· London

You will use Python (Pandas, NumPy, Scikit-learn), SQL, cloud-based MLOps platforms, and Generative AI/LLM/RAG tools to build predictive models and AI solutions that improve operational efficiency, service resilience, and customer outcomes for LSEG's financial markets infrastructure.

Databricks★3.0 (21)· London

You will work with Python, Scala, JavaScript/TypeScript, Apache Spark, and cloud ecosystems (AWS, Azure, GCP) to build production-grade data and AI solutions on the Databricks platform. In this hands-on role, you lead architecture and design decisions while embedding with customer teams to deliver end-to-end data pipelines, ML/AI models, and user-facing applications.

Flo Health★4.8 (26)· London

Lead a team of 6+ ML and backend engineers building production ML systems with TensorFlow, scikit-learn, CatBoost, and MLOps. You'll own Flo’s predictive lifetime value (pLTV) models, stand up Marketing Mix Modeling (MMM), and develop real-time campaign optimization algorithms to drive user acquisition strategy for the world’s #1 health and fitness app.

On Ag★2.9 (7)· London

Work with Python, PyTorch, JAX, TensorFlow, GCP/AWS, Kafka, and MLOps to build real-time personalization and recommendation engines. Lead data science initiatives that design, train, and deploy customer-level algorithms for On’s global D2C/e-commerce platform.

Fivetran★3.3 (8)· London

Senior Sales Engineer working with AWS, GCP, Azure, Snowflake, BigQuery, Databricks, Kubernetes, Docker, Podman, Grafana, Linux, Windows, Python, Java, and databases like Oracle, SQL Server, Postgres, MySQL, and NoSQL. The role supports Fivetran’s Commercial sales team by understanding customer data replication needs and leading proof-of-value processes for the company’s automated data pipeline and transformation solutions.

Fitch Solutions★3.0 (2)· London

As a Data Scientist at BMI (a Fitch Solutions business), you will design, build, and deploy quantitative models using Python and R (e.g., numpy, pandas, scikit, pytorch) to power advanced analytics. You will develop and maintain ML/NLP and data pipelines, working with Economists and Analysts to build risk models and generate insights from structured and unstructured data.

You will work with Python, PyTorch, JAX, TensorFlow, GCP/AWS, Kafka, and end-to-end MLOps to build and deploy batch and real-time machine learning models. As a Principal Data Scientist at On, you set the strategic direction for personalization and customer algorithms that directly impact the global D2C customer experience across web, app, and messaging.