Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

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

Work as a Python software engineer on the Risk team, building and delivering solutions using Python, REST APIs, and modern software architecture with cloud platforms such as AWS, Kubernetes, Docker, or Helm. You will address requirements from the Risk Management team and Trading desks at a tech-driven quantitative and systematic investment manager.

Builds cloud platforms for a systematic quant hedge fund's trading and research, using AWS (EC2, S3, VPC), Python/Bash, Jenkins/GitLab CI, Terraform/CloudFormation/AWS CDK, Docker, and Kubernetes to support digital asset and crypto systems.

Develop scalable data solutions using Python, SQL, and AWS for a Hedge Fund. The team delivers critical data across a global trading and research environment, transforming raw market and alternative datasets to support investment strategies.

Work with AWS (IAM, GuardDuty, Security Hub, Config, CloudTrail, KMS) and automation tools like Terraform/CloudFormation and Python scripting. The role strengthens cloud security and optimizes AWS infrastructure supporting high-performance research and trading platforms at a global quantitative trading firm.

You will work with Linux, AWS, Docker, Kubernetes, CI/CD pipelines, Python, Bash, and monitoring tools like Datadog, Prometheus, CloudWatch, or ELK. You will support and maintain the critical research and trading infrastructure for a quantitative hedge fund, acting as first-line support for platform-related issues.

You'll use Python, relational databases, data pipelines, and optionally cloud (AWS/GCP), containers, CI/CD, and TDD. The team builds a scalable trading and backtesting platform for quant researchers and portfolio managers, handling market and alternative data for simulation and live execution.

Develop end-to-end solutions in Python (pandas/numpy) for the Commodities RAD team, building data, research & trading platforms and tools for Portfolio Managers. Also use React/Angular for web frontends and SQL for databases.

Python, C++ and AWS with DevOps/CI/CD for real-time systems. You’ll build and enhance the quant tech stack for systematic crypto trading, integrating front-office systems and on-chain DeFi data feeds. You’ll also mentor junior developers.

Work with Python (pandas, NumPy) and tree-based machine learning to analyze high-frequency limit orderbook data and build predictive signals for proprietary trading. DV Trading provides liquidity to worldwide markets and hedging opportunities. You’ll collaborate with senior researchers and traders to refine production-ready models.

Durlston Partners· London

You'll use Java, Spring Boot, Kafka, and AWS (EKS, S3), plus PostgreSQL, SQL Server, and CI/CD. The team builds the core trade processing, reconciliation, and reporting platform for a leading systematic hedge fund’s multi-asset trading, collaborating closely with traders and quants.

You will design and build Python services and APIs using AWS (Lambda, S3, ECS/EKS, Step Functions, Aurora), Kafka, and PostgreSQL/SQL Server/Snowflake to support portfolio construction, trading, and analytics. This Investment Technology role turns research tools into production-grade platforms for Portfolio Managers and Quantitative Researchers across Equities, Fixed Income, and Alternatives.

You will use Python or C++ (with pandas, numpy, numba, multiprocessing, or GPU workflows) to design and refine systematic trading strategies, build volatility prediction and regime detection models, and run large-scale simulations. The team builds advanced algorithmic trading systems across FX and crypto, combining dynamic hedging, multi-agent grid logic, and high-frequency data insights.

Build and own the cloud infrastructure for live AI-driven trading systems, using AWS, Kubernetes, Terraform, Python, Kafka, PostgreSQL, Redis, and ClickHouse. You will design deployment pipelines, multi-region environments, and observability with Grafana, Prometheus, and Loki. This is a founding engineering role, giving you direct ownership of the platform and architecture.

You'll operate vulnerability scanning tools across on-premise, cloud, and hybrid environments, using scripting/automation (e.g., Python, PowerShell). You join Qube Research & Technologies, a global quantitative and systematic investment manager, working within the security function to run the vulnerability management programme across infrastructure and cloud.

Hudson River Trading★4.5 (2)· London

Work with Linux, SaltStack, Python, bash, and JIRA to design, automate, and optimize worldwide trading infrastructure. The team builds and maintains ultra low-latency operating systems and automation software that power HRT’s global 24/7 trading.

Hudson River Trading★4.5 (2)· London

Work with Linux systems (Debian/Ubuntu), SaltStack, shell (bash) scripting, JIRA, and TCP/IP networking on infrastructure supporting ultra low-latency trading. The team builds and maintains the production trading environment, managing hardware, kernel, and applications for global 24/7 operations.

Jupiter Asset Management★4.3 (4)· London

Work with Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, Azure cloud tools, large language models (LLMs), and Power BI. As a Data Scientist at this investment management firm, you build predictive models, research alternative data sources for alpha signals, and deliver data-driven solutions directly with investment professionals.

Invesco★3.9 (499)· London

Senior Engineer works with Python, SQL (PostgreSQL, SQL Server), AWS (Lambda, S3, ECS/EKS, Step Functions, Aurora), Kafka, CI/CD, and AI tools (Copilot, Claude, ChatGPT, Bedrock). The role designs and builds applications and data pipelines for Invesco’s ETF platform, supporting portfolio construction, trading, analytics, and operations across Equities, Fixed Income, and Alternatives.

You will work with Python, TypeScript, AWS (Cognito, Lambda, Fargate, API Gateway, S3, IAM), Terraform, PostgreSQL, and AI tools (Claude, GitHub Copilot, Cursor, LLM APIs). The team builds and evolves scalable microservices for BMLL Lab & Vantage, the company’s SaaS products for data science and visualisation on large financial datasets.

Castleton Commodities International★3.2 (24)· London

The engineer will work with Python, React, Angular, TypeScript, AWS, Snowflake, and CI/CD to build cloud-native tools for the front office. The team develops real-time analytics, backtesting engines, and market analysis tools to support energy commodity trading and risk management.

You will use Python, Pandas, and NumPy to prototype, design, and automate data pipelines for extracting, cleaning, and aggregating index and ETF data. The team collaborates with Quantitative Researchers and Traders to design and maintain datasets that drive systematic strategies for a global quantitative investment manager.

You will use Python with Pandas and NumPy to build and manage end-to-end data pipelines, extracting and cleaning fixed income market data for systematic strategies. The role bridges Research, Trading, and Engineering to design and automate datasets for bonds, rates, credit, and derivatives at a global quantitative investment manager.

The Data Scientist will use Python, Pandas, and NumPy to extract, clean, and aggregate data from raw sources, collaborating with Researchers, Traders, and Engineers. They join the Data Search & Analytics team at Qube Research & Technologies, a global quantitative investment manager applying a scientific, data-driven approach across liquid asset classes.