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.

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'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.

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.

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.

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.

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.

APL Logistics★3.3 (685)· London

You will work with Microsoft Fabric, Azure, Power Platform, ETL/ELT pipelines, APIs, and relational databases. This Regional Applications Team role manages data requests for EMEA and Americas, delivering data warehouses, pipelines, and automations for supply chain business users.

Design and build production-grade ML systems using MCP servers, recommendation systems, RAG pipelines, LLMs, and foundation models with Python, TensorFlow, PyTorch, FastAPI, and LangChain. You will own the end-to-end AI lifecycle for a sales data platform, deploying models into batch/real-time environments to drive forecasting, segmentation, and early warning systems. This role focuses on embedding context-aware intelligence into decision-making tools for business stakeholders.

You'll use Python, statistical modelling, machine learning, and privacy-preserving techniques (differential privacy, synthetic data, disclosure control) to build data-driven privacy and security controls. These controls protect participants in the UK's largest health research programme, which processes sensitive health and genetic data to enable safer, faster research.

Connected Places Catapult★3.0 (2)· London

You will apply statistical analysis, machine learning, AI, and generative AI (LLMs, agentic workflows) using Python, and work with R, Java, Terraform, and C++. As a Consultant Data Scientist, you deliver digital and data solutions to accelerate innovation for public bodies and infrastructure providers in transport and the built environment. You operate within a project-based team under guidance of a Head of Applied Data Science.

You'll lead a 4–5 person team building machine learning systems using Python, TensorFlow, PyTorch, JAX, AWS, Docker, and Kubernetes for Super's Playstack platform, which powers sports betting and gaming experiences across Europe and Latin America. The role combines technical contribution, project management, and people leadership, focusing on predictive analytics, personalization, fraud detection, and real-time recommendations that enhance customer engagement in online gambling and sports betting.

You will work with Java, Spring, and MongoDB to build micro-services using Gitlab and DevOps practices. Your backend engineering role supports Goldman Sachs’ financial platforms for trading, sales, and asset management.

You will work with Python, TensorFlow, PyTorch, and deep learning models on time series analysis, digital twins, and surrogate modelling. The company applies machine learning to real-world energy datasets to optimize performance and decision-making.

Goldman Sachs★3.9 (2.3k)· London

You will work on backend micro-service development using Java, Spring, and MongoDB. At Goldman Sachs, a global investment banking and securities firm, you’ll build scalable software, low-latency systems, and data-driven solutions for trading, sales, and asset management.

Work with the Databricks Data Intelligence Platform, Spark, PySpark, Python, Java or Scala, and major public cloud platforms (AWS, GCP, Azure). As a pre-sales engineer, you will demonstrate how Databricks' unified data and AI platform helps customers solve complex data challenges, collaborating with Account Executives and Senior Solutions Architects.

HeliosX★3.5 (19)· London

You'll work with Snowflake, Hex, Claude, and MLFlow or SageMaker in Python to build and deploy clinical prediction, risk stratification, and treatment-optimization models for a digital healthcare platform that personalizes patient journeys.

Design, develop, and optimize data pipelines using SQL, Python, Scala, Java, or Spark, along with ETL/ELT tools like Azure Data Factory, AWS Glue, and Apache Airflow, on cloud platforms such as Azure, AWS, or GCP. You will work with databases (SQL Server, Snowflake, MongoDB), big data technologies (Spark, Kafka, Databricks), and orchestration tools to build scalable cloud-based data platforms supporting enterprise analytics and machine learning.

IT Consultant role working on Agile/DevOps projects using Java, Object-Oriented, API, Python/Django, PostgreSQL, Pytest, and data science or financial systems tools. The consulting practice serves public and private sector clients, requiring client-facing project delivery, stakeholder engagement, and skill handover.