Cubist Quantitative Researcher in Singapore

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 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 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 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,

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Building processes, tools and frameworks to ingest, clean and deliver datasets Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams Creation of in-house, value added, derived data products for consumption by investment teams Engaging with vendors and internal stakeholders to understand characteristics of datasets Partnering closely with investment teams to ensure their data requirements are met Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams REQUIREMENTS PhD or Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required 5+ years of experience as a Data Scientist or similar role Experience working with large data sets including predictive modeling Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Intellectua

A Career with 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 We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal