You will work with Python, databases, APIs, and microservices to design and implement software for the Risk team’s core risk and PnL systems. The team supports risk analysis and reporting for the firm’s trading business, with a focus on Fixed Income products including bonds, swaps, futures, and options.

Quantitative researchers will develop mathematical, statistical, and machine-learning models for systematic trading, working in Python, with C++ and SQL as desirable, alongside large-scale data analysis. The role spans full research-to-production, collaborating with portfolio managers and engineers at a global quantitative investment firm. No team size is stated.

Senior Data Migration Engineer using SAP, SQL, and Python on a global ERP and middle-office transformation programme, migrating data for a large multi-site UK operation.

Python, Pandas, SQL (Snowflake, Postgres), AirFlow, Datadog, Grafana, Prometheus, and optionally PySpark/Dask. You will design and own a generalized system for business-critical reports from the backend data platform at a global prime brokerage and financing firm covering traditional and digital assets.

Deloitte★3.9 (14k)· London

You will work with Python, NumPy, Pandas, scikit-learn, LangChain, Hugging Face, LlamaIndex, Azure Machine Learning, Foundry, Git, and Agile practices. The team is Deloitte’s Tax Digital Innovation AI & Data Studio, which researches, builds, and delivers analytics and AI-driven solutions for tax and legal clients.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

Develops enterprise data platforms using Python, SQL, and Databricks, building ETL/ELT pipelines and working with data lakes and lakehouse architectures.

Lead and grow a Data Engineering function within an AI SaaS company, managing a small team of Data Engineers. You will use SQL and Python with modern data platform experience, reviewing code and technical decisions. This role involves delivering customer-facing data products and working with Product, AI, and Engineering teams.

Use Azure, Databricks, Python, PySpark, SQL and Azure Data Factory to build scalable ETL/ELT pipelines and cloud data solutions. You will design and maintain data systems for a London Market insurer’s enterprise platform, supporting smarter decisions across Underwriting, Finance and Operations.

Work with Python, SQL, SHAP, Airflow, PyFlink, BentoML, Git, Jenkins, Octopus, Docker, JIRA and MLFlow. As a Data Scientist at Zempler Bank, you develop algorithms to protect customers, widen credit access and improve financial outcomes. You implement and monitor models in production.