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.

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.

Bloomberg★3.8 (1.1k)· London

You will work with Python, SQL, PySpark, Pandas, NumPy, Airflow, dbt, Kafka, Iceberg, Trino, Superset, and data visualization tools. The Entity Data team manages core entity data for over 7 million public and private companies, supporting reference data and private markets; as Data Quality Manager you define and execute the quality strategy.

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.

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.

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 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.

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.

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.

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.

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.

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.

Work with Python, PyTorch, scipy, scikit-learn, numpy, pandas, MLflow, Docker, Kubernetes, Ray, and GCP to build and scale distributed compute for research workloads. Phaidra creates AI-powered control systems for the industrial sector using reinforcement learning to enable facilities to learn and improve automatically.

Work with Python, Pandas, NumPy, Polars, Flask/FastAPI, and optionally Databricks and AWS. You will build scalable tools for the Risk Division in an energy commodities trading environment, supporting traders and risk analysts by centralising data and improving reporting.

You'll use Python (with Pandas, NumPy, Polars, Flask/FastAPI) to build scalable tools and a platform for the Risk Division in energy trading. AWS cloud deployment is a plus.

Build and maintain in-house systems using Python, Pandas, NumPy, Plotly, FastAPI, AWS (Lambda, Step Functions, Cognito, ECS/Fargate, DynamoDB, CloudWatch, CDK), Docker and Kubernetes. You'll join Engelhart's Risk, Finance & Compliance technology team, delivering scalable solutions and integrations for commodity trading.

Work with Python, NumPy, pandas, SQL, dbt, Snowflake/Databricks, and LLMs to build and deploy ML models and agentic systems (function calling, multi-agent orchestration) for Planday’s scheduling and workforce management platform. You’ll ship production features on a small, high-impact team.

Barclays★3.9 (6.9k)· London

Lead a data science team at Barclays, working with Python, NumPy, Pandas, scikit-learn, and PyTorch to design, develop, and deploy production-grade AI and machine learning solutions. The role builds scalable, governed AI systems to extract insights from the bank’s data, informing strategic decisions and driving innovation. You will set technical direction and coach a team of data scientists.

Develop Python-based backend services and data pipelines for trading and risk management in investment banking, using Pandas, NumPy, SQL, Flask/FastAPI, and enterprise platforms like Quartz or SecDB. Work with large financial datasets to support risk, PnL, and trade lifecycle workflows, collaborating with quants, traders, and risk teams.

Build reliable data infrastructure using SQL, Python (pandas, NumPy, Apache Spark), open-source tools (Apache Kafka, Airflow/Dagster), relational databases (PostgreSQL, MySQL), Docker, Kubernetes and CI/CD. You will design ingestion pipelines, ETL/ELT processes and data models for an independent B2B energy supply company that provides risk management and energy solutions to UK industrial and commercial sectors.

You will work with Python, OpenAI, Azure OpenAI, LangChain, LangGraph, LangSmith, DeepEval, RAGAS, PromptTools, Docker, Kubernetes, and CI/CD. As part of a multidisciplinary AI engineering team on a major UK retail transformation programme, you will define and implement evaluation frameworks for enterprise-scale LLM applications and agentic AI systems.