Top Research Jobs in Singapore

Collaborate with quantitative researchers to analyze data, develop research tools, and enhance and maintain automated trading systems and algorithms. Build scalable software solutions using quantitative techniques to address complex financial problems. The role requires strong programming, Linux development experience, creative problem-solving, business-value prioritization, and effective stakeholder communication.

Develop high-performance C++ systems for systematic investing, including real-time data processing, low-latency trading execution, and machine-learning inference tools. Design scalable distributed systems and resilient data pipelines, maintain critical production platforms, and build greenfield solutions in collaboration with quantitative researchers. Ensure software correctness, reliability, performance, and fail-safe operation in live-market environments while aligning technical work with business value.

Conduct applied AI/ML research focused on software engineering, code quality, testing, and maintenance. Design experimental prototypes, develop Python-based AI/ML solutions, collaborate with researchers, engineers, and product managers, publish findings, participate in code reviews, and apply DevOps practices to maintain reliable research infrastructure.

Develop mathematical models and trading strategies, back test trading models, conduct research and statistical analysis for monetization systems.

As a Quantitative Research Analyst Intern, you will develop and improve trading models, conduct statistical analysis, and collaborate with team members in a data-driven environment.

Build high-performance research and production systems for AI-driven systematic trading. Responsibilities include developing low-latency C++ services, market-data and execution components, quantitative research pipelines, backtesting and simulation platforms, machine-learning model deployment workflows, and monitoring infrastructure. Optimize systems for throughput, latency, memory efficiency, resilience, and deterministic behavior while partnering with quantitative researchers and traders to productionize strategies and support live trading systems.

Conduct deep AI and quantitative research for electronic trading by pre-training Transformer and time-series foundation models on large-scale financial datasets. Develop representations, architectures, self-supervised objectives, distributed training systems, fine-tuning methods, and evaluation protocols for alpha generation, pricing, execution, market making, and risk management. Study scaling laws, transfer learning, robustness, data efficiency, inference cost, and latency while collaborating with infrastructure engineers to build reusable model-training and serving components.

An off-cycle quantitative trading and research internship focused on derivatives pricing, risk management, electronic execution, systematic trading, and portfolio optimization. The intern will build mathematical and machine learning models, develop pricing and hedging tools, research trading strategies, conduct scenario analysis, assess model risk, and implement high-performance analytics in production systems while collaborating with traders, risk managers, and banking teams.

Three-to-six-month quantitative trading and research internship developing mathematical models, pricing and risk tools, algorithmic trading strategies, portfolio analytics, and high-performance software. Interns apply machine learning and advanced statistics to derivatives pricing, hedging, electronic execution, market making, risk management, and systematic trading. The role involves quantitative research, scenario analysis, model validation, production implementation, collaboration with traders and risk managers, and communicating technical findings.

Conduct ML/DL research to develop predictive models from large market datasets, integrate models into systematic trading strategies, contribute to AI/ML libraries, and deploy production algo systems with P&L responsibility across FX, Rates, Commodities, and Credit.

Conduct China-focused semiconductor and AI supply-chain research, produce data-rich equity notes and weekly coverage, build bottoms-up financial models for Chinese foundries, fabless designers, memory and equipment firms, monitor disclosures and policy, engage industry contacts, and support institutional clients with timely analysis.

Perform financial and market research for the semiconductor and AI industries, build and maintain industry models, prepare reports and presentations, follow earnings and product trends, and represent the firm at regional conferences.

Supports research projects on ageing patterns in Asian populations and disease mechanisms. Coordinates timelines, milestones, documentation, meetings, collaborators, and project follow-ups. Oversees laboratory operations, equipment, materials, samples, procurement, inventory, records, compliance, safety, and ethical approvals. Provides administrative and operational support to the Principal Investigator and research team while ensuring projects are delivered accurately and on schedule.

Conduct literature reviews, identify weaknesses in existing AI models, develop and evaluate state-of-the-art methods, and compare results with current approaches. Prepare research papers and reports, build systems for agency and commercial partners, formulate hypotheses, design experiments, implement new modeling methods, and collaborate across disciplines. The role focuses on computer vision, detection, segmentation, diffusion models, deepfake classification, and image classification research.

Manages software and hardware technology projects from initiation through completion, including schedules, milestones, risks, resources, requirements, documentation, and stakeholder communications. Coordinates infrastructure deployments, data center installations, market-driven technology updates, and exchange compliance changes. Collaborates with technology departments, vendors, brokers, and exchanges while managing client expectations and project dependencies in a 24/7 trading environment.

Conduct research for quantum technology product design and engineering, including miniaturized NV sensors. Create detailed AutoCAD product drawings, apply optics and electronics knowledge, optimize quantum systems, and support laboratory administration and logistics. The role requires multidisciplinary research, product design, project leadership, and optics alignment experience.

Support lead analysts by maintaining industry models, perform financial analysis and three-statement modeling, research semiconductor and AI markets, prepare reports and presentations, represent the firm at APAC events, and contribute to newsletter articles.

Supports the HELIOS population health study by communicating with participants, guiding them through assessments, administering questionnaires, collecting samples and physiological data, maintaining study equipment and supplies, troubleshooting operational issues, and ensuring compliance with study protocols, Good Clinical Practice, HBRA requirements, and safety procedures. Collaborates with team leads and colleagues to provide accurate, efficient, and high-quality research participant care.

Recruit participants for a large-scale population health study by screening volunteers, scheduling research sessions, maintaining recruitment records, managing appointments, preparing reports, protecting participant confidentiality, and implementing outreach strategies. The role also leads social media and other communications to promote recruitment and study progress.

Conduct quantitative research on financial markets by discovering predictive patterns, developing statistical and machine learning models, running large-scale simulations and backtests, and translating research into production-ready trading signals. Interns collaborate with researchers and technologists, build research infrastructure and AI-powered agents, and complete rigorous projects from hypothesis through evaluation under realistic market conditions.

Conduct quantitative research on market behavior and trading strategies. Responsibilities include discovering predictive patterns, designing statistical and machine-learning models, building AI research agents, developing large-scale research infrastructure, running experiments and backtests, and translating findings into production-ready trading signals. Interns complete an end-to-end research project while collaborating with researchers and technologists.

Conduct quantitative research for systematic trading by analyzing market data, formulating and testing hypotheses, developing statistical and machine learning models, backtesting strategies, studying market microstructure, and partnering with technologists to deploy production-ready research and trading systems.

Develop high-frequency trading infrastructure, including exchange connectivity, low-latency network and systems programming, historical market-data and simulation systems, data-analysis tools, and risk-management and performance-tracking tools. The role requires strong C++ fundamentals, knowledge of algorithms and object-oriented programming, and familiarity with Linux, networking, high-throughput systems, blockchain, cryptography, and cryptocurrency technologies.

Develop and maintain quantitative market risk models, stress tests, and scenario analyses using high-frequency trading data. Design position, P&L, and exposure limits; manage governance, approvals, alerts, and escalations. Produce intraday and daily risk reports, analyze post-trade risk and drawdowns, and support capital allocation. Collaborate with quantitative researchers, technology, compliance, and regulatory teams on risk infrastructure and exchange-rule adherence.

Lead rigorous research involving frontier AI models, computational theory, physics, mathematical proofs, algorithms, numerical experiments, and high-performance simulations. Formulate open problems, validate and reproduce results, assess novelty and scientific significance, document model limitations, and recommend promising research directions. Establish standards for distinguishing genuine scientific progress from unsupported results while communicating findings through concise research memos.