Work with Microsoft Fabric (Lakehouses, Warehouses, Dataflows, Pipelines), Azure (SQL, Data Lake, Data Factory), SQL, Python, and REST API/SFTP to build ETL/ELT solutions. You will deliver modern data integration solutions for a diverse portfolio of clients within RSM’s Global VAT Team.

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.

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

Work with Python, DevOps, Linux, Pandas, NumPy, and relational/non-relational databases. You'll join the Vendor Data Group at a global quant firm to build and maintain mission-critical ETL/ELT data integration pipelines and tools for alternative commodity and macro data, collaborating with a trading team.

Develop end-to-end solutions in Python (pandas/numpy) for the Commodities RAD team, building data, research & trading platforms and tools for Portfolio Managers. Also use React/Angular for web frontends and SQL for databases.

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.

bp★3.8 (5.2k)· London

Work hands-on with Python, SQL, C#, Spark/PySpark, Palantir Foundry, planlogic EOS ETRM, Stonebranch, and AWS to build and maintain backend services, RESTful APIs, front-end components, and data pipelines. You will support bp’s LNG Energy Trading and Risk Management applications, including bespoke solutions for trade capture, operations, analytics, risk, reporting, and finance. This Staff Engineer role also includes mentoring and line management of the engineering team.

Prima★3.6 (45)· London

You'll work with Kafka, Flink, Spark, Databricks, Python, AWS, Redshift, PostgreSQL, and DevOps/CI-CD tools to build data products and pipelines for Prima's pricing and underwriting domain. The role bridges machine learning and engineering, focusing on data architecture, transformation, governance, and enabling teams to ingest, store, and serve data products. You'll join over 350 engineers across Prima, an online motor insurance provider trusted by 5 million drivers expanding in the UK and Spain.

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.

Senior Python Developer role building trading and risk platforms using Python, SQL, Pandas, NumPy, Flask/FastAPI/Django, PySpark, Unix/Linux shell scripting, and enterprise platforms like Quartz or SecDB. The team develops backend services, data pipelines, and risk applications for trade lifecycle, risk calculations, and regulatory reporting within investment banking.

You will use SQL, Python, Spark/PySpark, Pandas, orchestration tools, AWS/Azure platforms (Databricks, Redshift, Microsoft

You will work with Python, Django, Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, Elasticsearch, and Kubernetes, using AI tools like Claude Code and Cursor. You’ll shape the technical direction of a cloud-based property management platform handling payments, quoting, invoicing, booking, search, data pipelines, notifications, and fraud prevention. This is a leadership role bridging product vision and technical execution, guiding engineers toward delivery.

Work with Python (pandas, NumPy) and tree-based machine learning to analyze high-frequency limit orderbook data and build predictive signals for proprietary trading. DV Trading provides liquidity to worldwide markets and hedging opportunities. You’ll collaborate with senior researchers and traders to refine production-ready models.

Use Python, C#, .NET, TypeScript, React, Angular, SQL, PySpark, and agentic development tools (e.g., GitHub Copilot). You will be a Software Engineer III on the LNIP intelligence core platform, developing a semantic search API and maintaining an internal data curation tool.

You will use Python with Pandas, NumPy, and FastAPI/Flask to build backend services and APIs. You will also work with SQL, Linux/Unix, and risk analytics platforms to support trading, risk analysis, and trade processing for the front office.

You will work with C++ (including memory management) and Python (Pandas, NumPy) to build high-performance infrastructure, data pipelines, and quantitative trading systems. The team develops and optimizes simulation and backtesting tools and handles high-volume market data feeds.

You will use Python/PySpark, AWS S3/Glue/EMR, SageMaker, SQL, Git, CI/CD, Terraform/CDK, and Airflow/dbt/Step Functions to migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS SageMaker MLOps platform. You join a small Databricks workstream team building and migrating feature engineering, feature store, and data access layers for production pipelines in a regulated iGaming environment.

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.

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 (NumPy, SciPy), C++, large datasets, distributed systems, and high-performance computing concepts. The team builds high-performance trading and analytics platforms for a HFT leader that transforms sports data into competitive insight, and you will convert prototype models into production systems and optimize for low latency and scalability.

You will work with Python/PySpark, Databricks, AWS SageMaker, S3, Glue, Lake Formation, IAM, Terraform/CloudFormation/CDK, and Git/CI/CD. As part of a small delivery team, you will migrate ML data pipelines from Databricks to a SageMaker-based MLOps platform for a regulated iGaming client, building production pipelines and proving parity between platforms.

Build high-performance trading and analytics platforms using Python (NumPy, SciPy) and optionally C++, with large datasets, numerical computing, distributed systems, and high-performance computing. The team turns complex sports data into actionable insight for a HFT leader.

Work with Python, Pandas, NumPy, REST APIs, GCP, and MLOps tools on agentic AI, deep learning, NLP, or computer vision projects for Insight International (UK) Ltd.

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.

Allianz★3.8 (3.4k)· London

You will work with Docker, Kubernetes, Terraform, Azure, Azure DevOps, Python, SQL, PySpark, dbt, Microsoft Fabric, and SQLMesh. Joining a small stream-aligned agile team at an insurance company, you will build and maintain production-ready data and ML systems, including real-time API endpoints serving 10+ million daily requests.