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.

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.

You will work with the PyData stack (pandas, numpy, scikit-learn, XGBoost) and advanced ML methods like neural networks to build predictive models and proprietary metrics from high-frequency cricket tracking data. CricViz is a market leader in cricket data analysis, serving broadcasters, teams and gaming platforms.

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.

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'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.

Build REST and GraphQL APIs and MCP servers in Python (FastAPI, Flask) to expose ML models from Databricks to internal apps, CRM platforms, and AI agents at RBC. Work within the Data Science team to architect the serving layer, handling contract design, authentication, and documentation.

You will work with Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, cloud data tools (ideally Azure), and large language models (LLMs) to build predictive models and identify alpha signals. You will join the data science team of a leading investment management company.

You’ll build and ship user-facing apps primarily on Databricks Apps, using React, Vue, or Angular, and integrate with REST/GraphQL APIs served by the Data Science team. You are the technical lead on a team migrating from Power BI to custom applications, owning the full lifecycle while mentoring engineers on DevOps practices like Git and CI/CD.

Wise★3.5 (42)· London

You will build scalable systems for business onboarding and verification using Java or JVM languages, Spring framework, JDBC, and relational/non-relational databases with CI/CD pipelines and distributed systems. This engineering team owns end-to-end projects to automate verification, create flexible onboarding journeys, and manage compliance risks for Wise’s money-moving platform across Europe and the UK.

You'll build scalable AI data pipelines, cloud-native backend systems, and microservices using Python, FastAPI/Flask/Django, SQL, AWS/Azure, Docker, and Kubernetes. The company specialises in transforming AI research into secure, scalable production systems. You will also mentor junior engineers and contribute to architecture decisions.

You'll work with Java/JVM and Spring on the backend, React/JavaScript/TypeScript on the frontend, plus CI/CD, distributed systems, and relational/non-relational databases. You'll join Wise's Account Integrity team, building fraud-prevention and financial-crime detection systems to protect customer accounts. Wise is a global technology company for moving and managing money.

Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

You will work with PyTorch, TensorFlow, JAX, CNNs, Vision Transformers, and Python-based tools to evaluate and improve AI models for image recognition, object detection, segmentation, and visual reasoning. This contract role involves assessing model outputs, identifying failure modes, and refining training data for diverse visual domains.

Senior Python Engineer building trading, risk, and analytics applications using Python, Pandas, NumPy, FastAPI/Flask, SQL, and Linux/Unix. The role designs and develops scalable systems for risk analysis, trade processing, and data services, integrating with pricing and risk platforms for a financial services organisation.

This senior software engineer role uses Python, Snowflake, dbt, Kafka, Java, AWS, and Linux/Docker. You will build ELT pipelines and a streaming platform for tick data, consolidating legacy systems as part of the data engineering team for a systematic hedge fund.

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.

You'll use Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala to build high-performance, low-latency data systems. The Data Platform team in Global Markets owns the post-trade stack, processing high volumes of data and developing an AI-powered analytics UI/agent framework.

Python, FastAPI, Docker, DuckDB (nice-to-have), JSON Schema, Git, and RESTful APIs. You will design and ship ETL pipelines that transform raw bank data into the FIRE regulatory reporting standard. Suade is a regtech SaaS company automating compliance and risk solutions for financial institutions.

Work with Java/Spring, React, JavaScript/TypeScript, CI/CD pipelines, and distributed systems. You'll join the Account Integrity team building a globally scalable fraud prevention engine to protect customer accounts and prevent financial crime using machine learning and real-time monitoring.

You'll use Python, SQL, shell scripting, containerization, infrastructure-as-code tools, and Scala/Java or Python to build and maintain scalable data pipelines. You'll support a financial technology company's data infrastructure, contributing to AI/ML experiences and international applications. No team size is stated.

You will work with Python, R, SQL, Pandas, NumPy, Dask, SPSS, TensorFlow, PyTorch, scikit-learn, Hadoop, and Spark. As a Senior Data Engineer in IBM Consulting UK FutureNow, you lead advanced analytics projects and mentor junior engineers for clients in hybrid cloud and AI.

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.

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