Work with Python, SQL, cloud infrastructure, and ETL pipelines. You will develop skills across software engineering and data systems to support real-world sports-technology datasets.

You will build and maintain robust data infrastructure at a financial technology company, supporting international applications and cutting-edge AI/ML experiences. Your work ensures seamless platform operation at scale.

The listing names no specific technologies, languages, or frameworks. The role involves designing and building a state-of-the-art enterprise data platform that consolidates data from various sources, as part of a major client transformation. No team size or scope is stated.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

Work with Python, FastAPI, Docker, DuckDB, JSON Schema and Git to design, build and ship client ETL pipelines that map raw bank data onto the FIRE regulatory reporting standard. You will maintain a shared ETL framework, write validated mapping code, and mentor junior engineers at Suade, a regtech SaaS company automating compliance for financial institutions.

You will use SQL, Python, Azure, and Snowflake to design and maintain data pipelines, analytical datasets, and calculation logic. This role supports a global marketing advisory firm by building the data foundations that underpin audience and marketing intelligence offerings for clients.

You will work with Snowflake, DBT, SQL, GitHub Enterprise, market data platforms and AI-assisted tooling such as GitHub Copilot and Snowflake Cortex AI. You will design, build and optimise scalable data solutions and data models for a financial services programme transforming investment decision-making and regulatory reporting.

Analytics Engineer role using SQL, dbt, Databricks, Kafka, Databricks Workflows, and data activation tools like Hightouch. You'll build data products and pipelines supporting ClearScore's 26 million users in making financial decisions, serving the operational platform and CRM.

You'll work with time-series data, supervised and unsupervised ML, CI/CD, version control, and tools like Claude Code, MLflow, and cloud platforms (Azure, AWS, GCP) with MongoDB. Ceto provides operational intelligence for maritime, analyzing ship data to predict mechanical failures through anomaly detection and degradation forecasting.

Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

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.

Wise★3.5 (42)· London

You will build predictive customer LTV and Marketing Mix Models using customer behavior and product usage data, working with Data Analysts and Marketeers to identify growth opportunities and optimize marketing investment for Wise, a global technology company building a network for moving money across borders.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

You will use TensorFlow or PyTorch, Python, and CV/graphics libraries, plus 3D engines like Unreal or Unity, to develop generative models for graphics and video. As part of the Visual Computing Group, you'll design neural networks and ML for PlayStation's game rendering and live

Build and scale Nxera Pharma’s computational drug discovery platform, working with Python, AWS, Docker, Prefect, GitHub Actions, Terraform/CDK, PostgreSQL, and Linux. You'll develop backend services, cloud infrastructure, CI/CD pipelines, and workflow orchestration alongside computational chemists and ML engineers. No team size is stated.

Senior C# .NET developer role on the Data team of a global energy trading house, building data platforms for market data collection, real-time streaming, governance, and machine learning, with a focus on data consumption and publishing. Tech stack includes C#, .NET, ASP.NET, Angular, SQL Server/Oracle, Docker, Kafka, Azure Service Bus, Grafana, and Azure DevOps.

Design and maintain scalable data integrations using Azure Logic Apps, Storage Accounts, API Management, Microsoft Fabric, and Azure DevOps for CI/CD. You will lead integration pipelines that enable data movement across Bell, ensuring governance and reliability. The role also includes mentoring junior team members.

Data Engineer role using Azure Data Factory, Databricks, Azure SQL, T-SQL, Python, SSIS, and CI/CD, supporting legacy SQL Server warehouses and migrating to Azure. Work spans finance, actuarial, and AI claims initiatives within the Data team at Canopius, a global specialty lines (re)insurer.

You will use SQL, Python, BI tools (PowerBI, Looker, Tableau, etc.), and spreadsheets. As a Data Analyst on the Fraud team at Moniepoint, an all

This Data Analyst role involves performing ad-hoc data extractions using SQL and supporting digital analytics with Google Analytics and Tag Manager. Transform is an end-to-end transformation partner that builds and operates systems for clients in the public sector and dynamic brands.

Design, develop and optimise scalable data solutions using Azure Databricks, Azure Data Factory and Scala. This role processes large-scale datasets, builds ETL pipelines and works with stakeholders within a London-based long-term data engineering programme.

Develop KDB+/q applications for real-time market data and scalable infrastructure supporting quantitative strategies at a leading global hedge fund. You will build high-performance research, analytics, and trading platforms, working with Quants and Traders to solve low-latency engineering challenges.

Work with advanced Python, large complex datasets, and a proprietary technology stack including high-performance trading systems and data platforms. As a Quantitative Researcher, you will lead independent research to discover and deploy alpha-generating systematic investment strategies across global equity markets.

Uses Python, SQL, Pandas, NumPy, SciPy, Scikit-learn, PyTorch/TensorFlow, Git, Linux, and cloud computing. Researches and develops alpha signals, systematic strategies, and portfolio construction for global equity markets at a systematic trading firm.

Python, PyTorch, Ray, distributed systems, cloud and GPU infrastructure. You will build platforms and services supporting ML training and deployment, develop tooling for data processing and model lifecycle, and maintain distributed systems for a well-funded AI company.