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.

Escalent★3.6 (38)· London

You’ll work with Python and frameworks like Django, Flask, or FastAPI, building RESTful APIs, microservices, and data pipelines while integrating AI/ML models and LLM APIs. Tech includes SQL/NoSQL databases, AWS/Azure, Docker, Kubernetes, and CI/CD. Escalent is a data analytics and advisory firm, and you’ll develop AI-powered applications and intelligent workflows in its cloud-native environment.

Build pipelines and models using Python, TypeScript, and Next.js to transform unstructured data into structured, queryable formats for an AI platform supporting private-equity reasoning. You will join a six-person founding technical team focused on NLP, information extraction, and representation learning.

You will build evaluation, experimentation, and observability pipelines using Python and platforms like Braintrust, LangSmith, Arize, and Weights & Biases, plus design LLM-as-judge and human-in-the-loop scoring. The role focuses on AI-native consulting for clients like PayPal and adidas, including production monitoring, quality signal detection, and cost attribution. You'll also wire evaluation gates into CI/CD pipelines for the AI Engineering team.

You will work with Python, NumPy, SciPy, simulation modelling, optimisation under uncertainty, cloud deployment, and machine learning. The team builds an AI operating system for secure environments, taking complex scientific models from prototype to production across government and commercial programmes.

This Senior Full Stack Developer role involves Python, TypeScript, React, SQL, PostgreSQL, Large Language Models (LLMs), prompt engineering, and AI coding tools. You will own and develop the company’s flagship AI platform, building data pipelines and full-stack features that solve strategic challenges for clients. You will work within a small engineering team.

You will work with kdb+, q, Python or Java, APIs (REST, messaging), Linux, AWS/GCP, Docker/Podman, and CI/CD. You will develop, test and maintain kdb+ applications and supporting services for market data and analytics on a Client Engineering team for a FinTech leader. You will also mentor junior developers.

You will work with AWS (Lambda, S3, SQS, SNS, Step Functions, DynamoDB, CloudWatch, EMR, MSK/Kafka, Redshift), PySpark, Python, Apache Iceberg, Parquet, and XML/ASN.1 parsers. The role builds scalable cloud-based data pipelines for telecom network performance data, focusing on high-throughput ingestion, ETL/ELT workflows, schema management, and optimizing delivery to Redshift and ClickHouse.

SQL and Python are used to develop pricing strategies, analyse marketing and conversion funnel performance, and evaluate product expansion opportunities. The role supports a fintech unicorn that revolutionises the credit and savings landscape. Mentoring and coaching junior analysts is also part of the position, though the team’s size is unspecified.

Use Python, scikit-learn, TensorFlow, PyTorch, and geospatial tools like QGIS and ArcGIS. As a Machine Learning Engineer at a technology consultancy, you will design, build, and deploy ML models

You’ll work with QGIS, ArcGIS, GeoPandas, Rasterio, GDAL, Python, and AI-assisted development tools. As part of the ANALYTIQ team, you’ll build geospatial models, reusable scripts, data pipelines, and interactive web tools to accelerate Systemiq’s sustainability projects across energy, materials, nature, and finance.

You'll work with Python, LLMs, Generative AI, RAG architectures, Agentic AI, Conversational AI, Voice AI, Speech-to-Text and Text-to-Speech technologies. This role designs, builds and deploys AI-powered customer and business solutions across Conversational AI, Agentic AI, Voice AI and intelligent automation for a leading international consumer technology and digital services organisation.

You will develop and deploy LLM-powered applications using PyTorch, SGLang, and PEFT/LoRA, building and fine-tuning embedding and reranking models. You will work on an early-stage platform that combines machine learning with real-world trading workflows to transform specialised financial markets. You will join a small engineering team with direct collaboration alongside founders and traders.

Develop agentic AI applications with Python, LLMs (OpenAI, Anthropic), and frameworks like LangGraph or CrewAI, building REST APIs and integrating cloud services (AWS, Azure, GCP). This contract role involves AI solutions for a client in financial services, working with structured financial data and collaborating with product and engineering teams.

Senior Software Developer role in the Data team of a global energy trading house, working on data-consumption and publishing platforms using C#, .NET, ASP.NET, Angular, SQL Server, Oracle, Docker, Grafana, Kafka, Azure Service Bus, and Azure DevOps. Responsible for end-to-end delivery, mentoring, and architectural direction.

You'll work with Python, FastAPI/Django/Flask, PostgreSQL, cloud platforms (Azure/AWS/GCP), and build scalable REST APIs and data pipelines for an enterprise AI platform used by financial institutions.