Jobs at WorldQuant

Develop and maintain large-scale, production-quality C++ software on Linux for quantitative research and portfolio production platforms. Build distributed systems and high-performance applications using strong data structures, algorithms, and concurrency patterns. Collaborate with researchers and portfolio managers, work independently, and contribute to scalable computation, graph data, and streaming or dataflow systems.

Build and maintain scalable backend services, APIs, and components for an alpha testing and production framework. Design new systems, enhance existing platforms, automate CI/CD, and improve reliability and performance. Collaborate with agile engineering and operations teams while using Python, databases, messaging systems, Linux, and open-source technologies.

Conduct quantitative investment research to develop predictive signals and computer-based models for global financial markets. Explore market data, identify inefficiencies, create financial strategies, and collaborate on alpha production. The role requires strong analytical and programming skills, independent problem-solving, attention to detail, and an interest in finance. Candidates must be highly accomplished academically, proficient in Python and C/C++ on Unix/Linux, and able to communicate complex concepts clearly.

Lead development of complex data pipelines, AI/ML systems, and software solutions. Provide technical leadership, mentor engineers, conduct code reviews, make architectural decisions, and collaborate with technical and non-technical stakeholders. Maintain hands-on Python development using scalable data engineering practices, cloud platforms, containerization, CI/CD, and machine learning frameworks. Experience with large language models and AI agents is highly desirable.

Provides level-one operational support to front-office teams and portfolio managers, including regional start-of-day checks, exception and alert management, trading outage resolution, issue escalation, workflow improvement, and global activity reconciliation. Handles counterparty breaks and supports daily portfolio and treasury operations. Requires flexibility for night shifts and strong problem-solving, communication, and attention to detail.

Conduct ML research to produce predictive trading signals, design deep learning architectures, apply LLM-based agentic methods, implement signal compression and combination, build model frameworks for investment use, and collaborate with portfolio managers and researchers.

Monitor automated execution across equities, foreign exchange, futures, and other asset classes. Provide first-line support for execution issues, improve automation and liquidity integration, analyze large datasets, reduce implementation costs, and collaborate with portfolio managers, brokers, compliance, risk, and senior management.

Research and develop quantitative signals from high-frequency equity market data. Responsibilities include feature engineering, exploratory data analysis, simulation and backtesting, validation across markets and regimes, signal implementation, and collaboration with quantitative researchers and engineers. The role also involves applying machine learning and deep learning to market microstructure, building production-quality low-latency code, exploring data sources, and developing tools to automate software development, testing, and deployment workflows.

Conduct quantitative finance research by creating predictive alphas and utilization algorithms, studying academic literature, and identifying new research domains. Analyze and improve the BRAIN platform, design and test features and datasets, support business strategy, engage users and consultants, and deliver training. The role requires strong quantitative reasoning, programming skills, financial-market interest, creativity, persistence, and effective English communication.

Design, develop, and maintain systems, interfaces, and tools for portfolio management. Collaborate with portfolio managers and developers to translate requirements, investigate and resolve issues, monitor and support production systems, participate in code reviews, testing, and documentation, and improve team productivity using modern tools and LLMs.

Build and operate scalable, reliable production systems for an investment pipeline. Responsibilities include monitoring performance, managing CI/CD and release processes, containerizing and scaling services, maintaining hardware and filesystems, applying security practices, supporting system design, responding to incidents, and improving operational efficiency in collaboration with engineering teams.

Troubleshoot complex user issues involving data, technology, and trading signals; collect and communicate user feedback to Product, Sales, and Marketing. Develop backend systems focused on performance, load sequencing, software quality, security, access management, storage, data versioning, and server-side web applications.

Lead HR for Vietnam offices (Hanoi, HCM): strategic HR business partnering, ensure legal compliance, oversee full employee lifecycle, drive engagement, retention, workforce planning, compensation benchmarking, HR analytics, Workday data integrity, and advise leadership on performance and employee relations.

Lead development of complex data pipelines and AI/ML systems, provide technical leadership and mentorship, design scalable architectures, write and review code, and collaborate across teams to deploy production-grade solutions involving LLMs and data engineering.

Design, implement, test and deploy high-performance C++ software on Linux to support large-scale quantitative research and production trading. Own technical challenges for scalable distributed systems, work with researchers and portfolio managers, and optimize data structures, algorithms and concurrency for production-grade performance.

Lead the development of AI-driven solutions, architect scalable AI products, mentor junior engineers, and integrate AI across the organization.

The Senior Python Engineer will lead complex data pipelines and AI/ML systems, manage technical objectives, mentor junior team members, and drive architectural decisions.

Lead the development of complex data pipelines and AI/ML systems, manage technical objectives, mentor junior engineers, and drive architectural decisions.

Develop and maintain web applications across the tech stack, designing backend services, APIs, and user interfaces while ensuring performance and scalability.

Develop and research predictive alphas and algorithms on the BRAIN crowdsourcing platform, improve platform functionality, design new datasets/features, support business development, train and engage external users and consultants.