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/Responsibilities: We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology. Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave. Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation. Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features. Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. Requirements: PhD or PhD candidate in machine learning, computer science, statistics, or a related field Experience with sequential modeling and time
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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. JOB DESCRIPTION Researchers are responsible for independently conducting quantitative finance 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. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX Strong analytical and quantitative skills Demonstrated ability to conduct independent research utilizing large data sets Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that yo
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. JOB DESCRIPTION Researchers are responsible for independently conducting quantitative finance 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. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX Strong analytical and quantitative skills Demonstrated ability to conduct independent research utilizing large data sets Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that yo
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 Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative research with a focus on predictive models. You will be trained in all aspects of systematic trading from idea generation all the way to practical trading considerations. Successful hires will ultimately become thought leaders within our collaborative research group. RESPONSIBILITIES Conduct original quantitative alpha signal research Follow, digest and analyze the latest academic research Manage all aspects of the research process, including idea generation, data analysis, hypothesis development and testing, alpha discovery, trading strategy generation, backtesting and portfolio analysis Build analytical tools to supplement our shared research framework REQUIRMENTS B.S., M.S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. Programming in Python (or comparable language) and working knowledge of SQL Strong analytical and quantitative skills. Willingness to take ownership of his/her work. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Detail-oriented. Prior experience in the financial services industry is not required. A 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 Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative research with a focus on predictive models. You will be trained in all aspects of systematic trading from idea generation all the way to practical trading considerations. Successful hires will ultimately become thought leaders within our collaborative research group. RESPONSIBILITIES Conduct original quantitative alpha signal research Follow, digest and analyze the latest academic research Manage all aspects of the research process, including idea generation, data analysis, hypothesis development and testing, alpha discovery, trading strategy generation, backtesting and portfolio analysis Build analytical tools to supplement our shared research framework REQUIRMENTS B.S., M.S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. Programming in Python (or comparable language) and working knowledge of SQL Strong analytical and quantitative skills. Willingness to take ownership of his/her work. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Detail-oriented. Prior experience in the financial services industry is not required. A 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 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,
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,
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,
JOB TITLE Reference Data Engineer A Career with point72’s Cubist TEAM 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 Develop, test, and maintain software applications using .NET Full Stack technologies. Write clean, scalable, and efficient code in Python for various applications. Collaborate with cross-functional teams to define, design, and ship new features. Implement and manage CI/CD pipelines and other DevOps practices to ensure smooth deployment and operation of software solutions. Participate in code reviews and contribute to a culture of continuous improvement. Troubleshoot and resolve software defects and issues in a timely manner. Stay up to date with emerging technologies and industry trends to enhance skills and knowledge. What’s REQUIRED We are looking for a motivated and skilled Software Engineer with experience in .NET Full Stack development, Python, and DevOps. You should also have: Bachelor’s or master’s degree in computer science, engineering, statistics or a related field. 3+ years of experience in .NET Full Stack development and Python programming. Basic understanding and practical experience with DevOps tools and methodologies. Strong problem-solving skills and attention to detail. Excellent communication skills and the ability to work collaboratively in a team environment. Eagerness to learn and adapt to new technologies and challenges. Commitment to the highest ethical standards. About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its inves
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. About the team: The team is focused on systematic equity trading. It is established, yet still pre-trade, offering an exciting opportunity to join at an early stage and be involved in a broad range of development areas. The team members come from a mixture of quant analyst and development backgrounds, using the combination of skills to achieve a common goal. All team members are based in the London office five days a week to maximize communication and interaction. Role and Responsibilities: An ideal growth role to suit a developer looking for additional responsibilities and independence. Responsibilities may include: • Building components for all aspects of live trading and research environments. • Driving automation and robustness of our processes. • Developing robust data checking and handling procedures. • Monitoring and troubleshooting any issues that should arise. • Shared responsibility for timely and correct operation of trading systems. Requirements: • Bachelor’s degree or equivalent in computer science or other STEM discipline • 2+ years commercial experience with Python and its data science libraries on Linux. • Pragmatic balance between attention to detail and delivery focus. • Ability to work with ambiguous requirements. • Self-driven, owning problems while knowing when to seek advice. • Knowledge of finance and trading systems a plus. • Experience with a systems programming language (
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. About our Team: KEPL is a fast-growing team at Cubist Systematic Strategies. We are specialized in medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms, including: D.E. Shaw, Two Sigma, Citadel, Meta, Google, etc. We have an open and collaborative culture, and we value rigorous research and innovative technologies. Please send CVs to [email protected] with “2026 KEPL QD Application” in the subject line. Role: We are looking for a quantitative software developer to join our team and contribute to multiple initiatives that aim to expand our business. The candidate should be passionate about financial market, data and technology. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative trading. Responsibilities: Improve data ETL pipeline and build tools to analyze new data efficiently. Build technologies to bolster research & trading efficiency. Expand to new markets and asset classes. Manage day-to-day operations in a fast-paced environment. Requirements Master/PhD degree in math, computer science, engineering, or other related fields. 1-3 years of professional experience in software development or data science/analytics. Strong combination of quantitative skills and programming skills. Proficiency in Python; knowledge of common data analytics tools (e.g., SQL, pandas) is a plus. Familiarity with the Linux environment. Excellent written and verbal communication skills. Willing to work in a fast-paced start-
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.
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 alpha research requires mastery of multiple domains. The best research requires original research ideas, good intuition, strong data analysis skills, and good research planning. Our research directly drives our investment decisions. This role is highly selective. We have a long history of training extraordinarily talented academic researchers to succeed in the investment services industry. Prior experience in the financial services industry is not required. RESPONSIBILITIES Provide research assistance to full-time researchers Assist with data collection and preliminary analysis Follow, digest, analyze and improve upon the latest academic research DESIRABLE CANDIDATES Ph.D. candidates in finance, economics, mathematics, statistics, physics, computer science, or other quantitative discipline. Programming in any of the following: R, Python, or C++. Experience with SQL. Solid research experience in the field of the candidate’s specialty. Strong analytical and quantitative skills. Detail-oriented. Demonstrated ability to learn and apply new methodologies to real life problems. Willingness to take ownership of his/her work. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Prior experience in the financial services industry is not required.
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 Our research center in Singapore is seeking an experienced researcher with a strong background in alpha research. In this highly selective role you will have access to abundant research resources and exciting opportunities to discover high quality alpha signals that directly drive our investment decisions. RESPONSIBILITIES Conduct original quantitative alpha signal research Manage all aspects of the research process, including data analysis, alpha signal discovery, backtesting, trading idea generation, alpha signal/portfolio analysis and the management of production code Evaluate new datasets for alpha potential Follow, digest, analyze and improve upon the latest academic research DESIRABLE CANDIDATES 2+ years of research experience in Equities. Ph.D. or M.S. in finance, accounting, economics, mathematics, statistics, physics, computer science, operations research, or another quantitative discipline. Programming in any of the following: R, Python, or C++. Experience with SQL. Demonstrated ability to learn and apply new methodologies to alpha generation. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Detail-oriented. Willingness to take ownership of his/her work.
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 researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi
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