BlackRock★3.8 (632)· London

You will design and develop distributed Java applications using Spring, Spring Boot, REST APIs, streaming technologies like Kafka and Apache Flink, relational databases (MS SQL Server, PostgreSQL, Sybase ASE), and Microsoft Azure. You will join BlackRock Global Markets’ In-Business technology team, building reliable, scalable technology to support the firm’s investment processes and platform architecture.

You will deploy ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data) to production environments, using Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow. PhysicsX builds an AI-driven simulation software stack for engineering and manufacturing.

You'll work with Python (pandas, OOP), SQL (PostgreSQL, Snowflake), CI/CD pipelines, Git, and GitHub. You'll develop and support in-house fund management tools that assist Fund Managers in managing funds for Legal & General's asset management division.

Atlassian★3.9 (61)· London

Leading a distributed EMEA team, you'll use Python, JavaScript, APIs, and microservices to build AI-powered solutions with generative AI, LLMs, and agent-based frameworks. The Forward Deployed Engineering team partners with top organizations to solve complex problems using Atlassian’s AI capabilities.

Build and enhance data-driven solutions using Scala, Python, Java, Hadoop, and Spark (Hive nice to have) in a financial services environment. Work with cross-functional teams on scalable, high-performance applications, participating in code reviews and performance optimization.

Use Python (pandas, NumPy, SciPy, matplotlib/seaborn) and SQL with cloud-based data tools and large language models. Build predictive and statistical models to identify alpha signals from alternative data for a leading investment manager with a global presence.

You will execute A/B tests, multivariate tests, and personalisation campaigns using platforms like Optimizely, VWO, and Adobe Target, working with analytics suites such as Google Analytics 4 and Adobe Analytics, plus CMS and CDP tools. The role drives daily execution of the Rapid Iteration & Optimisation framework, collaborating with Paid Media, CX, and Development teams to deliver performance-enhancing site updates.

Works with A/B testing tools (Optimizely, VWO, Adobe Target), analytics (GA4, Adobe Analytics) and CDPs (Segment, Tealium), plus basic HTML, CSS, JS. Executes daily high-velocity site optimisation and continuous improvement for global clients within WPP Enterprise Solutions, collaborating with Paid Media, CX, and Development teams.

You will work with Python, FastAPI/Flask, PostgreSQL, MySQL, BigQuery, GCP and/or AWS, and IAC/CI/CD tools to build production-grade data pipelines and MLOps infrastructure. You’ll join Ki’s commercial performance insights squad to upgrade algorithm decision data to a versioned event stream and support a Monte Carlo simulation engine for an algorithmic insurance carrier. The role is in an agile, cross-functional squad.

RBC★3.9 (5.5k)· London

You will drive the BI team's transition from Power BI to custom Databricks Apps, using React/Vue/Angular, REST, GraphQL, MCP, and DevOps tools (Git, CI/CD, GitHub Actions/Azure DevOps). You will build user-facing data visualisations and interactive analytics. You will mentor engineers and set technical standards.

RBC★3.9 (5.5k)· London

You will design, build, and maintain REST and GraphQL APIs and MCP servers using Python (FastAPI, Flask) serving ML models from Databricks for internal apps, CRM platforms, AI agents, and LLM applications. You will build middleware, prototype applications, and mentor junior colleagues in a team reporting to the Director, Data Science.

Arup★4.0 (352)· London

Python, Git/GitHub, pytest/unittest, CI/CD pipelines, AWS/GCP/Azure, Terraform/Docker, MATSim, Java, and PopulationSim. The Transport Modelling and City Modelling Lab teams build agent-based and activity-based models to solve urban transport challenges, using data and software engineering to plan future mobility systems.

You'll work with Python, PostgreSQL, MySQL, BigQuery, FastAPI, Flask, GCP/AWS, and CI/CD pipelines. You'll join the commercial performance insights squad to build data pipelines and event streams for monitoring algorithmic insurance underwriting, including Monte Carlo simulation.

You will work with Java microservices, Spring Boot, Python, SQL, Snowflake, dbt, Airflow, LangChain, Sagemaker, and MLflow. The data science team builds ML solutions for risk-based decisioning, pricing, and operational automation in insurtech/fintech. This is a hands-on leadership role—you will lead and develop the team while setting technical standards.

You’ll work with Python, PostgreSQL, MySQL, BigQuery, FastAPI/Flask, and GCP/AWS to build production data pipelines and MLOps infrastructure for Ki’s algorithmic insurance platform. You’ll act as a data engineer in the commercial performance insights squad, designing systems that monitor algorithmic underwriting decisions in real time.

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.

You'll build RAG systems, multi-agent infrastructure, and evaluation frameworks using Python (Django/FastAPI), relational databases, Docker, Kubernetes, and CI/CD. The company develops AI workflow automation for financial institutions, handling document processing and natural-language data retrieval under strict compliance standards. This role reports directly to the founders.

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’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.