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. WHAT YOU'LL DO The Quant Developer will be responsible for building and maintaining the research infrastructure and backtesting frameworks that support quantitative research, working closely with researchers to translate research ideas into robust, scalable, and maintainable research systems. The role spans multiple areas, including system design, data pipeline development, and the development of research and backtesting frameworks. WHAT'S REQUIRED Background in Electrical Engineering, Computer Science, or a related field, with 3+ years of software development experience as a software engineer. Strong programming ability in C++ and Python. Solid command of CI/CD practices and tooling, with the ability to design and maintain automated testing and build pipelines for research and backtesting environments. Practical knowledge and hands-on experience with distributed computing and distributed job scheduling / task assignment. Excellent analytical and engineering problem-solving skills. Demonstrated ability to work independently on large datasets and large codebases. A strong team player who works closely with researchers to translate research ideas into stable, maintainable research systems. Willingness to take ownership of your work, able to operate both independently and within a small team, while remaining careful, detail-oriented, and capable of performing well under pressure. Strong English communication skills. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provid
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Role We are looking for an experienced Macro Quant Researcher to join our team in Taipei. Responsibilities Develop macro-focused systematic trading strategies in liquid secondary markets. Conduct research to identify data-driven signals and market inefficiencies. Collaborate with team members on research and development initiatives. Requirements B.S., M.S., or Ph.D. degree in economics, finance, computer science, physics, or other quantitative discipline. 2+ years of experience in quantitative research or systematic trading at a bank, hedge fund, or asset manager. Experience with systematic trading strategies for any secondary market product (e.g., Taiwan index futures, BTC, etc.) using tools beyond Excel or MultiCharts. Proficiency in Python or C++ and familiarity with database query languages (SQL or NoSQL). Demonstrable ability to conduct independent research utilizing large datasets. Detail-oriented, willingness to take ownership of his/her work, and ability to work both independently and within a small team. Commitment to the highest ethical standards.
Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models. 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 Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring. Desirable Candidates M.S., Ph.D., or Ph.D. candidates in finance, computer science, mathematics, physics, or other quantitative discipline. Programming in any of the following: C++, C#, Java, or Python. Strong analytical and quantitative skills. Keen interest in quantitative research and metrics driven decision making. Demonstrated ability to conduct independent research utilizing large data sets. Detail-oriented. Passion for spotting trends in data. Willingness to take ownership of his/her work, working both independently and within a small team. Ability to work under pressure. Prior experience developing, researching, or implementing quantitative models for equities is preferred, but not required. We will provide training for new researchers without finance backgrounds.
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