Equity Financing Trader, Asia Pacific

Point72 Academy 2026 Investment Analyst Program for Experienced Professionals – Hong Kong We’re training the next generation of Point72 discretionary investment professionals. The Point72 Academy Program is a ten-month paid training program designed to introduce you to the buy-side and prepare you for a potential career as a Fundamental Equity Financial Analyst at Point72. Upon successfully graduating from the Academy, you will have the opportunity to be placed in a role on a fundamental equity investing team. As an analyst at Point72, you will benefit from our mentorship culture and ongoing professional development resources that are dedicated to your continued growth beyond the Academy. WHAT YOU’LL DO: Learn the fundamental research and analysis skills needed to be an analyst at Point72 and apply intellectual curiosity in a role that values creativity, autonomy, and analytical rigor. Develop sophisticated company analysis and modeling skills from our Academy faculty, investment professionals and professors from some of the world’s leading universities. Learn statistics, accounting, financial modeling, data analysis, coding, and more. Complete a compliance training curriculum to prepare you for an analyst role. For all Academy Associates, at least a portion of this training will take place in our New York City office Apply the skills you’ve developed to real-life situations as you rotate with two investing teams. Gain firsthand experience and valuable mentorship from our investment professionals during your rotations. Upon Successful Graduation: The Analyst Role Upon the successful completion of the Academy, you’ll have the opportunity to interview for an equity research analyst role at Point72, where you’ll work closely with your portfolio manager and team to develop a deep understanding of companies across industries and around the world. Through fundamental research and financial analysis, you’ll attempt to see change before it happens and tu

Job Responsibilities A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure Desirable Candidates Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure DESIRABLE CANDIDATES Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

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 The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance. RESPONSIBILITIES Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas. Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization. Maintaining and improving portfolio trading in production environments. REQUIREMENTS Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline. 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus. Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning. Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas. Ability to work both independently and collaboratively within a team. Commitment to the highest ethical standards.

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets, including spot and derivatives. We are looking for an experienced Systematic Trader to develop, operate, and continuously improve systematic strategies in fast-moving electronic markets. Responsibilities: Operate and manage systematic trading strategies and frameworks across prediction markets, equities, and crypto, including spot, perpetuals, futures, options, and other derivatives. Monitor live trading, P&L, positions, risk, and execution performance. Research, backtest, deploy, and improve systematic trading strategies. Identify new trading opportunities across markets, products, exchanges, and venues. Analyze strategy and execution performance, including fills, slippage, adverse selection, transaction costs, and latency. Optimize strategy parameters, position sizing, execution, and risk controls. Work closely with quantitative developers and researchers to implement new strategies and improve trading systems. Participate in local trading coverage and rotating weekend coverage. Requirements: 4+ years of experience in systematic, quantitative, electronic, proprietary, or market-making trading. Demonstrated experience developing, operating, or improving profitable trading strategies. Strong understanding of market microstructure, execution, and risk management. Strong Python programming and quantitative data-analysis skills. Experience working with large market and trading datasets; SQL experience is preferred. Strong analytical and problem-solving skills, with the ability to take ownership in fast-moving markets. Master's or PhD degree in a quantitative discipline, or equivalent relevant quantitative experience. Preferred: Experience trading in one or m

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets . We are looking for a Trading Operations & Support Analyst to support live systematic trading, ensure smooth day-to-day operations, and help improve the reliability and efficiency of our trading systems and processes. Responsibilities: Monitor live trading systems, strategies, orders, positions, P&L, and risk. Act as the first line of support for trading, execution, exchange connectivity, and production issues. Investigate and resolve order, position, P&L, reconciliation, and trading-system exceptions. Coordinate with traders, quantitative developers, exchanges, brokers, and other counterparties to resolve live trading issues. Support strategy deployments, system releases, testing, and production changes. Monitor exchange and market events, outages, connectivity issues, and other operational risks. Analyze trading and operational metrics to identify issues and improve processes. Develop tools and automation to improve monitoring, reconciliation, reporting, and trading operations. Maintain operational procedures and controls for production trading. Participate in local trading coverage and rotating weekend coverage. Requirements: 3+ years of experience in electronic trading, trade support, trading operations, production support, or a related role. Strong understanding of electronic trading, order lifecycle, positions, P&L, and risk. Ability to troubleshoot issues calmly and effectively in a fast-moving production environment. Strong Python or scripting skills; SQL experience is preferred. Experience working with large trading or market datasets. Strong analytical, communication,