You'll work with Python, SQL, ETL/ELT, FastAPI, and AI/LLMs to build a mission‑critical Data Migration Platform that connects to legacy CRMs and onboard financial agencies at scale.

Write Python and FastAPI to build a real-time intelligence platform for private markets, used by venture capital and private equity firms to analyze live data and make faster investment decisions.

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'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.

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.

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.

You will work with GenAI tools like OpenAI, LangChain, Hugging Face, Vertex AI, and Bedrock, plus Python, PyTorch, TensorFlow, vector databases (FAISS, Pinecone), and cloud platforms. The Data Science Team builds and deploys LLM-based applications for enterprise use cases such as customer service, document automation, summarization, and knowledge retrieval.

You'll design, build, and maintain scalable AI data pipelines, cloud-native backend systems, and distributed services using Python, REST APIs, and microservices with FastAPI, Flask, or Django. You'll productionise Machine Learning, NLP, and Generative AI models, work with SQL databases, AWS/Azure, Docker, and Kubernetes, and mentor juniors. The company specialises in AI and data engineering, transforming AI research into production systems.

Build scalable solutions using C#, .NET and SQL for a global hedge fund’s trading, risk, pricing, and quantitative research platforms. You will collaborate with quantitative and investment teams on real-time, mission-critical systems.

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.

Lineten★2.6 (5)· London

Build cloud-native services using C#, .NET, Azure, and Microsoft Fabric with a Medallion architecture, while integrating AI/LLMs and automating infrastructure. You’ll own end-to-end development, data pipelines, and site reliability for a small startup team building internal and external data self-service solutions.

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 will engineer agentic AI decision loops, retrieval and embedding pipelines, and rigorous testing frameworks using Python, orchestration frameworks, vector databases, and semantic search, with JVM languages as a plus. Own the full model lifecycle, balancing fine-tuning specialized models versus frontier LLMs, while mentoring on production-grade ML standards. This is a senior ML engineering role for iForce Connect, building deep, integrated AI systems that navigate complex datasets.

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 build cloud-native apps with C#/.NET and Azure, design Microsoft Fabric and Medallion data pipelines, handle ETL/ELT, SRE, and integrate LLMs via OpenAI/Azure OpenAI. Based at startup Lineten Ltd., you’ll join a small team enabling internal and external data self-service analytics.

Work with Python, SQL, Scikit-learn, TensorFlow/PyTorch, Pandas, and NumPy to build machine learning models. As a Data Scientist at a consultancy, you will deliver data-driven projects for enterprise clients across the UK.

You'll build production-grade AI systems from the ground up at a global investment firm, working with Python, FastAPI, LangGraph/LangChain, vector/graph databases, OpenAI/Anthropic LLMs, Azure AI, and CI/CD. As the founding AI hire, you'll own RAG pipelines, multi-agent orchestration, semantic search, and internal AI platforms.

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.