Lead the design and architecture of cloud-native, distributed systems, APIs, and data platforms powering Fasanara Open Quant, a quantitative multi-strategy multi-manager hedge fund. Build core investment, portfolio, risk, and data technology while working directly with portfolio managers, quantitative researchers, and traders.

Java, Kafka, AMQ, Kubernetes, AWS, and MongoDB. You will join a tight-knit team building and supporting systematic trading models for a sports betting hedge fund.

Work with Python, modern AI platforms, LLMs, APIs, distributed systems, MCPs, and tool-use frameworks to build AI-powered applications, assistants, and agentic workflows. You will drive AI adoption across QRT’s High Frequency Trading business, creating tools that improve productivity in research, development, and trading operations.

Invesco★3.9 (499)· London

You will research and develop APIs, high-performance computing algorithms, and portfolio construction tools for the Invesco Vision® platform, using classical statistics, ML, and Generative AI. You will build multi-asset portfolios and employ multi-period simulation tools as part of the Portfolio Construction and Engineering team at the investment firm Invesco.

Work with advanced quantitative research tools and techniques to develop alpha-generating systematic macro strategies. This role is on a lean Systematic Macro Team at a global, multi-strategy hedge fund.

You will work with Python, SQL, and financial data pipelines to build APIs and high-performance computing algorithms for Invesco Vision®. The team performs quantitative research, constructs multi-asset portfolios, and develops prediction methods using classical statistics, machine learning, and Generative AI. This role sits within the Portfolio Construction and Engineering team.

Design and optimize high-performance cash equity algorithmic trading systems using Java, Rust, Python, and kdb. The role supports internal and agency electronic execution desks and includes microstructure research, backtesting, and low-latency platform performance analysis.

You will work with Python, machine learning, and predictive modelling to research, develop, and deploy alpha signals and predictive models. You will lead a key part of the European systematic equities alpha research team at a global proprietary trading firm, managing researchers and driving alpha initiatives from idea to production.

You will lead research and deployment of alpha signals and predictive models, using Python and machine-learning frameworks for systematic, intraday trading strategies. You will manage and grow part of the European alpha research team for a global proprietary trading firm. The team size is not specified.

Lead Alpha Researcher role blending hands-on research with leadership; work includes Python, machine learning, predictive modelling, and statistical validation to develop alpha signals for systematic equities. You’ll manage part of the European alpha research team, driving global initiatives for IMC, a global trading firm.

Graduate will use Python, C++, Java, C#, or KDB+/q to build next-generation trading systems, research platforms, and quantitative models for a global investment fund.

Build sophisticated trading and analytics platforms using React, TypeScript, JavaScript, WebSockets, GraphQL, and REST. You’ll create high-performance, real-time data visualizations for traders and quantitative researchers within a leading quantitative investment firm.

Citi★3.9 (21k)· London

Design and optimize high-performance cash equity algorithmic trading platforms using Java, Rust, Python, and kdb. Conduct microstructure research, build backtesting frameworks, and monitor platform performance for ultra-low latency. Work on the electronic execution team supporting internal and agency trading desks.

Kepler Cheuvreux★2.2 (6)· London

This role involves monitoring and optimizing algorithmic trading performance, smart order routing, and delivering execution analytics for institutional clients, using Python and SQL for large trading datasets. The trader will partner with Quant Development and Engineering teams to enhance algorithms and SOR capabilities at Kepler Cheuvreux’s electronic execution platform (KCx).

You will design and build cloud-native systems, APIs, data platforms, and resilient data pipelines for Fasanara Open Quant, a technology-led multi-manager hedge fund that tracks independent quant trading teams. As Quant Technology Lead, you'll also integrate market data providers, prime brokers, and custodians into the platform.

PhD students in quantitative fields will develop systematic trading strategies using Python (NumPy, Pandas) and statistical/machine-learning techniques to analyze financial datasets. They'll build and test quantitative models, support research infrastructure, and present findings to portfolio managers and researchers at a quantitative-trading firm specializing in algorithmic trading and systematic investing.

Use Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, Azure cloud tools, and large language models to identify alpha signals from alternative data. Build and maintain predictive models and develop reproducible data science processes for a leading investment management company serving global investors.

You will work with Python and its data science libraries on Linux, with cloud compute and containers as a plus. The role builds components for live trading and research environments within Cubist Systematic Strategies, which deploys systematic, computer-driven trading strategies across equities, futures, and foreign exchange.

Point72★3.6 (15)· London

You will work with Python and its data science libraries on Linux, plus systems programming languages like C++ or Rust, cloud compute and containers. The team focuses on systematic equity trading within Cubist Systematic Strategies, building components for live trading and research environments.

Work with Python (C++, Rust, or Go for latency-critical paths), AWS, Terraform, PostgreSQL/TimescaleDB, Kafka, Redis, ClickHouse, and Grafana/Prometheus/Loki. You own the production infrastructure for a stealth systematic trading and AI research lab building low-latency decision engines that operate in live markets.

S&P Global★3.9 (1.7k)· London

Work with Python for repeatable analytical workflows, complex datasets, back-testing and quantitative research on equity and digital-asset index concepts within S&P Dow Jones Indices’ Index Design team. The role supports the full design lifecycle — from data validation and methodology development to stakeholder discussions — for systematic, scalable index solutions.

You will use Python, REST APIs, and cloud platforms such as AWS, Kubernetes, Docker, and Helm. As part of the Risk team at a tech-driven quantitative investment manager, you will build and deliver solutions for Risk Management and Trading desks.

Invesco★3.9 (499)· London

The Senior Associate will own and enhance the fund-level model, supporting transactions, asset management, and portfolio strategy for a pan-European real estate fund. The role involves complex financial modeling, scenario analysis, and collaborating with local transaction and asset management teams across Europe.

T. Rowe Price★3.6 (709)· London

Work with SQL, Python, data warehouses, analytical platforms, UML, Jira, and Confluence to define and deliver strategic investment data capabilities for portfolio management, research, trading, analytics, and AI within the Investment Data Strategy & Architecture team at a global asset manager.

Millennium Management★3.8 (21)· London

Work with Python, C++, Docker, Kubernetes, Ceph, MongoDB, Kafka, Numpy, Polars, Scikitlearn, and Pytorch on a small, collaborative systematic trading team. The role involves developing real-time event-driven systems for alpha research, feature engineering, portfolio construction, and trade execution.