Quantitative Trader - Singapore

About BlockTech As a Quantitative Trader on our Singapore trading floor, you’ll own positions and PnL end-to-end from interpreting live market flow and liquidity through tuning and intervening in our automated systems, all the way to shaping the next generation of execution logic and trading tools. You’ll sit shoulder-to-shoulder with Quantitative Researchers, Quantitative Developers, and Software Engineers, and your decisions will directly drive how we trade across venues. The role Managing and monitoring Delta1 positions across multiple venues, owning the PnL and risk that comes with them Reading live market flow, liquidity conditions, and market events, and translating that read into concrete trading and execution decisions Tuning and parameterising our automated and semi-automated systems, and knowing when to step in to manage risk or capture an opportunity Improving execution quality and market-making performance through data-driven analysis of strategy behaviour Designing and specifying the trading tools, dashboards, and analytics that the desk relies on to make decisions Collaborating closely with researchers, developers, and engineers to sharpen models, infrastructure, and execution logic, and shaping the roadmap for new trading initiatives What we’re looking for 3+ years of experience as a Quantitative Trader and/or Quantitative Researcher in a professional trading environment, with demonstrated PnL responsibility on linear (Delta1) products across multiple venues Hands-on experience operating automated and semi-automated trading systems under live conditions: monitoring, tuning, and intervening when it matters Strong analytical instincts: you can take a messy dataset of fills and quotes and turn it into a concrete execution improvement A deep, intuitive grasp of market microstructure and the ability to explain why a strategy works, not just that it does Proficiency in Python for analysis, tooling, and interaction with trading systems An ownership mindset:

About Graviton Research Capital: Graviton Research Capital is a cutting-edge high-frequency trading (HFT) firm that leverages technology, quantitative research and algorithms to trade in global markets. Our team consists of world-class technologists, researchers and traders who collaborate to push the boundaries of automated trading. Role Overview : We’re looking for a Central Execution Trader to join our Singapore team. This role interfaces with, and acts as the communication hub for all brokers and exchanges on behalf of the firm externally, as well as technology, quantitative researchers, risk management, compliance, and business development teams internally. In this role, you’ll be building and refining systems that keep our live trading running flawlessly—where milliseconds make the difference. From designing real-time monitoring tools to automating critical workflows, you’ll be at the heart of ensuring smooth and efficient trade execution. Key Responsibilities: Act as the first line of defense in the events of alerts, rejects, and outages, and act as the primary point of contact for brokers and exchanges as the run point on all live issues that impact trading, undertaking risk-reducing trades when required, and ensuring end of day processes. Build and enhance real-time trade monitoring systems for live and post-trade environments, driving faster data analysis and quicker issue resolution. Automate critical processes like position reconciliation, and locates borrowing, cutting down manual effort and boosting operational efficiency. Conducted advanced trading algorithm analyses, optimizing execution strategies to improve trading efficiency. Leveraged expertise in systematic trading systems to enhance financial data management and operational efficiency. Work closely with traders, exchanges/PBs, developers and risk managers to enhance operational workflows and reduce processing times. Supported trade operations by monitoring and resolving trade discrepancie

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. What you’ll work on Collaborating closely with traders to translate research insights into systematic trading strategies Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we’re looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuit

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m

Graviton Research Capital is one of the largest quantitative trading firms in APAC, with a strong footprint across 40+ global exchanges and a rapidly growing presence across multiple geographies. We are a bootstrapped firm with a long-term vision, focused on building high-performance teams that operate at scale in some of the world’s most competitive markets. Since our inception, we have built a team of exceptional researchers, portfolio managers, and technologists. We are seeking an Operations Analyst ( middle office ) for our team in Singapore. What You Will Do: Oversee daily trade bookings, position and P&L reconciliations, settlement challenges, and corporate action events Ensure accurate and timely delivery of reports on trades, positions, cash holdings, costs, and P&L attribution Manage all operational aspects throughout the trade lifecycle, from initiation to settlement Liase with counterparties, custodians, and prime brokers to on-board new businesses and address daily issues Identify and drive process improvement initiatives, focusing on increasing operational efficiency and scalability. Design and implement automated solutions that streamline workflows using best practices in data management and automation. What You Need to Succeed: 2 to 5 years of Middle Office/Operations experience, preferably from a buy-side environment (Hedge funds, Prop Trading) or Prime brokerage Solid product knowledge in listed equities (a must), ETFs, derivatives, and FX Familiarity with Asian securities markets and their respective regulations is preferred Proficient in Excel, with practical experience in VBA, SQL, and Python Demonstrated experience in process improvements and designing automated solutions, ideally within a trading environment Excellent problem-solving skills with a proactive approach to identifying and addressing areas for improvement Why Join Graviton? Work in a high-performance, data-driven trading environmen

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,