Affiliate Business Development Manager Jobs

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

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: Cubist is looking for a support engineer/quantitative developer who will work on a growing L2/L3 support team for quantitative trading systems, high‑frequency trading infrastructure, real time analytics, and research infrastructure. This role will require close collaboration with multiple teams at Cubist, including multiple Portfolio Manager (PM) teams, Central Research Technology, and Execution Services. The role offers career growth through the opportunity to work on the development of the underlying systems. Role/Responsibilities: Troubleshooting/resolution of quantitative trading systems and other live analytics processes System monitoring, including development of better processes and tools New feature development in Python/C++ Configuration and change management Onboarding assistance Requirements: 2+ years of professional support and/or software engineering experience Experience with trading systems support (co-located low-latency systems a strong plus) Fluency with C++, Python and SQL Familiarity with software delivery lifecycle and production deployment Cloud experience is a strong plus Team player and strong communicator

About Cubist Cubist Systematic Strategies, an affiliate of Point72, is one of the world’s premier investment firms. The firm 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 The Central Research Technology team, which builds strategic solutions for research and live trading of quantitative strategies across multiple frequencies and products, is seeking a highly talented intern to work with the team in January. This is a unique opportunity to help design and build the next generation of research and quant trading systems for Cubist. Desirable Candidates Undergraduate or graduate candidates in computer science or engineering Significant experience in Python and/or C++ Interest in open source research tools for data science and machine learning Basic knowledge of linux, git, conda, and CI processes Knowledge of cloud, databases and distributed or streaming compute is a plus Reasonable quantitative and statistical skills Experience with Finance preferred Clear, concise, and proactive communicator Detail oriented and quick learner in a fast-paced environment Team player with strong pride of ownership 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. RESPONSIBILITIES: Building components for both live trading and simulation Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards Maintaining and updating the platform, ensuring its stability, robustness, and security Developing robust data checking and storage procedures Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements REQUIREMENTS: Bachelor’s degree or higher in computer science or other STEM discipline Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax) Proficiency with Linux Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control) Strong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpful Proficiency with C/C++ is a plus Experience with designing and implementing trading systems 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: A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team. Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in the equities market End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation Identify and evaluate new datasets for stock return prediction Maintain and improve portfolio trading in a production environment Contribute to the analysis framework for scalable research Requirements: MS or PhD in a quantitative discipline 0-2 years of professional work experience A background in financial markets is not necessary, but an interest in the field is essential Proven expertise in Python and handling large datasets Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus Highly motivated, curious, and critical thinker Collaborative mindset with strong independent research abilities 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/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

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 (