Top Research Jobs in Singapore

Lead equity research coverage across ASEAN telecommunications, media, technology, internet, fintech, and digital infrastructure companies. Develop financial models, valuation analyses, investment views, research reports, earnings updates, and thematic publications. Engage with company management, investors, and clients; monitor competitive and regulatory developments; collaborate with sales and trading; and mentor junior team members.

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.

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.

Design and evaluate software-only protocols for verifying AI datacenter compute and memory usage. The role involves developing challenge kernels, microbenchmarking GPUs, measuring latency across cluster topologies, studying compression and hidden capacity, red-teaming timing assumptions, and publishing findings. Work spans GPU performance engineering, adversarial measurement, cryptographic protocol design, hardware security, and LLM inference systems.

Expression of interest for future research scientist or research engineer opportunities at Neo Research. The organization seeks candidates working in model evaluations, AI alignment, interpretability, machine learning, large language model engineering, agentic systems, or related fields applicable to frontier AI safety. Prior AI safety experience is not required. Reading and writing Mandarin is a plus.

Build practical prototypes for AI verification, including distinguishing GPU training from inference workloads and exploring zero-knowledge proofs and privacy-preserving evaluations. The role spans ML engineering, inference pipelines, algorithms, frontend demonstrations, cybersecurity, and collaboration with external experts. It also involves technical communications and engagement with policymakers and international partners in an ambiguous, early-stage environment.

Research Engineer/Scientist developing and testing confidential-computing verification systems for AI datacenters. Responsibilities include analyzing GPU attestation guarantees, designing attested-result registries and verification clients, building privacy-preserving logging and evaluation pipelines, chaining attestations, integrating multiple accelerator platforms, collaborating with cryptographers and hardware-security experts, red-teaming systems, and publishing results.

Conduct research using dense seismic arrays and distributed acoustic sensing for seismic, coastal hazard, and environmental monitoring. Develop detection, characterization, and modelling methodologies; plan and execute geophysical field deployments; publish findings; mentor students; and collaborate with researchers and external partners. The role requires expertise in seismic data processing, dense array analysis, seismoacoustics, signal processing, waveform modelling, and programming in Python or MATLAB.

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.

Research and develop novel AI models, algorithms, and systems; validate them through rigorous experiments and large-scale distributed training; and transition prototypes into production. The role involves deep learning, LLM pre-training and alignment, efficient GPU/TPU utilization, scientific analysis, technical writing, mentoring, code and paper reviews, open-source contributions, and end-to-end project ownership.

Build reliable software and infrastructure for frontier AI agent research, including environment execution, trajectory collection, evaluations, experiment orchestration, data pipelines, and observability. Partner with research engineers to turn prototypes into reusable, tested systems; improve reproducibility, scalability, cost efficiency, and recovery from failed runs; and own infrastructure from design through operation.

Conduct quantitative research for global equities alpha strategies by developing and validating signals, implementing research papers, building reusable tools, writing production-quality Python code, communicating findings, and transforming raw datasets into clean research inputs. The role is designed for graduate-level students and may lead to a full-time Quantitative Researcher position.

Supports a multi-site clinical research programme by coordinating participant recruitment, consent, scheduling, questionnaire assessments, biospecimen collection, data management, documentation, site communications, ethics compliance, and safety reporting across participating clinics.

Conduct research in machine intelligence, deep learning, foundation models, and AI applications. Analyze algorithms on large-scale datasets, implement scalable prototypes, collaborate on systems from research through production, and develop solutions for real-world problems. The intern will investigate research tools and methods, contribute to technology transfer, and potentially support patents, publications, standards, internal tools, and product or business collaborations.

Develop tools and infrastructure for training language models in interactive environments, implement novel methods in language modeling, reinforcement learning and multi-agent systems, and contribute to publications and open-source projects.

Lead and mentor a research team developing agentic AI (planning, RL, LLMs, diffusion, multi-agent systems). Define and execute research strategy, track state-of-the-art work, and build external AI community relationships to position Skyfall as a research leader.