Citi★3.9 (21k)· London

You will work with C++, C#, .NET, Java, Python, kdb, and SQL to develop analytics libraries and pricing models using Monte Carlo methods and PDE solvers. The role focuses on creating quantitative models for Citi’s cross-asset XVA and capital analytics, supporting trading business pricing and risk-management. You will collaborate with Traders, Structurers, and technology professionals.

You'll work with Python, NumPy, SciPy, Pandas, PyTorch, JAX, and deep learning frameworks to build models using operator learning, geometric deep learning, or generative models. PhysicsX is building an AI-driven simulation software stack for multi-physics engineering and manufacturing across aerospace, energy, and other advanced industries.

JPMorgan★3.9 (20k)· London

Work with KDB, Q, AWS, and optionally Terraform, Kubernetes, Python, C, C++, or Java. Develop and maintain applications storing large Options data sets for real-time and historical access within JPMorgan’s Equities Trading Data & Analytics team, migrating to AWS and re-architecting systems.

Wise★3.5 (42)· London

You will work with Java, Spring Boot, AWS, Apache Kafka, and potentially Trino. The Pricing Core team builds and maintains the main pricing platform that enables Wise to price its products, processing over 100 million requests daily across critical paths.

Atlassian★3.9 (61)· London

Leads a team of forward-deployed engineers building AI-powered solutions with Python, JavaScript, APIs, microservices, and LLMs. The team partners directly with top organizations to apply Atlassian’s AI capabilities to solve real-world problems.

Junior Software Engineer role supporting in-house fund management tools for Legal & General's Index Analytics team, using Python (pandas, OOP), SQL (PostgreSQL, Snowflake), git/GitHub, and supporting CI/CD pipelines. The work covers portfolio performance analysis, process automation, and data pipelines for fund managers. Exposure to JavaScript, Flask/FastAPI is helpful.

You’ll build and maintain scalable data pipelines and implement observability, monitoring, and data quality checks using Python, SQL, shell scripting, containerization, and IaC tools (with Scala/Java preferred). You’ll support AI/ML-driven financial technology platforms at a global fintech company, collaborating with product engineering, data science, and business teams.

American Express★4.1 (9.7k)· London

AI Researcher at American Express will develop advanced ML models for structured data (tabular, sequences, graphs) using transformer, reinforcement learning, and causal techniques, with Python, Spark, C/C++, Java, and Google Cloud tools like Vertex AI and BigQuery. The role sits in AI Labs within Credit and Fraud Risk, driving research into production for credit, fraud, and marketing decisions. Leadership scope is not specified.

Work with Python, pandas, numpy, scikit-learn, XGBoost, LightGBM, neural networks, SQL, Git, and AWS/GCP to develop proprietary metrics and predictive models from high-frequency cricket tracking data. The role transforms complex data into commercial

Genpact★3.8 (7.9k)· London

You will lead a team of data engineers building scalable Big Data pipelines and ETL processes using Java, Databricks, Snowflake, and cloud computing, all within an Agile methodology. The role supports Genpact, an advanced technology services company delivering AI and data solutions for global enterprises.

Zeta Global★2.6 (44)· London

You will work with Scala/Java, relational and NoSQL databases, container-based solutions, ZIO, Akka, Play Framework, AWS, and Terraform. You will provide technical leadership for the Addressability part of the Zeta Marketing Platform (ZMP), an AI-powered marketing cloud that unifies identity, intelligence, and omnichannel activation for marketers.

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.

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.

Design, build, and deploy AI-driven workflows, automation solutions, and intelligent agents using Copilot Studio, Microsoft Fabric, Power Automate, Logic Apps, Python, JavaScript, PowerShell, and Azure automation tools. The role operates in a Forward Deployed Engineer model within Jensten’s Data & Technology team, delivering practical AI use cases across the insurance intermediary group.

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.

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.

Works with Python, Agentic AI tools, and automation frameworks to develop and maintain automation solutions for the Reporting Center of Excellence, including running over 500 existing processes across enterprise data sources. Mentors junior engineers and coordinates with business collaborators to identify automation opportunities.

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.