Research Jobs in New York, USA

<p></p> <h3>A Career with Point72’s Technology Team</h3> <p>As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications.</p> <p>As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. </p> <h3>What you’ll do</h3> <ul> <li>Develop, implement, and maintain front‑end user interfaces using modern web technologies (Typescript, HTML, CSS, Angular/React).</li> <li>Extend and/or develop microservices in Node.js or C#</li> <li>Provide data to microservices from data sources such as SQL, Mongo, and Databricks</li> <li>Build and enhance platform-level AI capabilities by integrating and extending MCP, agents, tools</li> <li>Collaborate closely with UX designers, product managers, and platform engineers to deliver seamless end‑to‑end user experiences</li> <li>Troubleshoot issues, perform code reviews, and ensure adherence to coding standards and best practices</li> <li>Prevent, identify, and fix risks and issues caused by application development changes or infrastructure changes</li> <li>Coordinate weekly and emergency releases with other Technology teams</li> <li>Engaging team and monitoring each stage of the project</li> <li>Determine and oversee consistent testing, evaluation, and troubleshooting of all products in all stages of completion</li> </ul> <h3>What’s required</h3> <ul> <li>Understanding of the hedge fund business and environment</li> <li>Technical knowledge in Typescript, Node.JS, C#, HTML, and CSS</li> <li>Self-motivated and dedicated mindset, with the ability to take ownership and deliver within a reasonable timeline</li> <li>Passion for building mission-critical, elegantly engineered, and scalable code following clean coding practices (SOLID, continuous refactoring, testing)</li> <li>Professional and precise communication skills</li> <li>Ability to design self-contained, reusable, and testable modules and components<

<p><strong>ABOUT PROPRIETARY RESEARCH</strong></p> <p>On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions our investment professionals care about most. We look for other bright, motivated, and collaborative people to join our team and grow with us—more than 90% of the leaders in our group were promoted from within.</p> <p><strong>WHAT YOU'LL DO</strong></p> <p>Senior Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly extract insights from large, complex structured and unstructured data sets. As a senior member of our Data Engineering team, you will help set technical direction and work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will:</p> <ul> <li>Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery</li> <li>Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers</li> <li>Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies</li> <li>Build and support visualization and exploration capabilities around our big data sets</li> </ul> <p><strong>WHAT EXCITES YOU</strong></p> <ul> <li>Technical leadership through hands-on development</li> <li>Having a broad impact on architecture and team processes</li> <li>Transforming large unstructured, data sets into valuable investment research inputs</li> <li>Learning and working with industry-leading cloud-computing technologies</li> <li>Speaking with experts both inside and outside the firm to understand data needs and offerings</li> <li>Fast-paced work environments that at times require switching gears to address the needs of the business</li> <li>Working as part of a cross-functional team made up of Investment, Research, and Compliance professionals</li> </ul> <p><strong>WHAT EXCITES US</strong></p> <ul> <li>A

<p><strong>A Career with point72’s Surveillance team</strong></p> <p>Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.</p> <p><strong> </strong></p> <p><strong>What you’ll do</strong></p> <p>As a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:</p> <ul> <li>Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.</li> <li>Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.</li> <li>Work with sparse data and apply techniques to improve model accuracy and generalization.</li> <li>Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.</li> <li>Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.</li> <li>Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.</li> </ul> <p><strong> </strong></p> <p><strong>What’s REQUIRED</strong></p> <ul> <li>PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.</li> <li>6+ years of experience build

<p><strong>Role:</strong></p> <p>The Quant Researcher will report to a Stamford based Portfolio Manager and will focus on:</p> <ul> <li>Building, running, and maintaining power dispatch model for ERCOT and other major US ISOs</li> <li>Driving the model’s inputs and architecture to efficiently simulate power grid conditions and marginal pricing</li> <li>Continuously testing and improving the model, ensuring it accurately replicates historical conditions and effectively analyzes forward scenarios</li> <li>Communicating the model’s results and limitations to the wider investment team</li> </ul> <p><strong>Responsibilities:</strong></p> <ul> <li>Formulate and build a power dispatch model using Python and a commercial solver</li> <li>Collaborate with the PM to optimize model inputs and architecture</li> <li>Ensure the model replicates grid operations from historical conditions</li> <li>Suggest model improvements to decrease forecast error and improve scenario handling</li> <li>Regularly run the model and maintain up-to-date outputs in an internal database</li> <li>Communicate results and limitations to the wider investment team, including publishing results to team dashboards</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li>Master or PhD in operations research, electrical engineering, applied mathematics, or a related quantitative field</li> <li>5+ years of direct experience building power dispatch models (SCUC/SCED) using optimization solvers (Gurobi, CPLEX, etc.)</li> <li>Knowledge of power plant dispatch, grid operations (including capacity and AS obligations), and LMP pricing in US power markets</li> <li>Experience using SQL and timeseries databases</li> <li>Proficiency in Python and Git; additional experience with an OOP language a strong plus</li> <li>Domain knowledge in ERCOT, PJM, or CAISO preferred</li> </ul> <p><strong>About Point72:</strong></p> <p>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 investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.</p> <p> </p>

<h3>Role/Responsibilities</h3> <ul> <li>Research and develop in-house trading strategies, used by both discretionary and quantitative traders.</li> <li>Conduct quantitative research on market microstructure, applying knowledge to improve trading algorithm and identify market anomalies.</li> <li>Develop and maintain predictive models to optimize trade execution and minimize transaction costs, utilizing both linear and non-linear techniques.</li> <li>Collaborate with cross-functional teams, including portfolio managers and researchers, to design and implement solutions for the trading strategies.</li> <li>Stay current and report on changes in market microstructure.</li> </ul> <h3>Requirements</h3> <ul> <li>Master's degree or higher in a quantitative field such as Finance, Mathematics, Statistics, Computer Science, or a related discipline.</li> <li>A minimum of 2 years of experience in quantitative research, building statistical models for intraday study.</li> <li>Solid understanding of market impact.</li> <li>Proficiency in programming languages such as Python and C++. Experience in AWS is preferred.</li> <li>Strong knowledge in macro products, including FX and bonds, is a plus.</li> <li>Commitment to the highest ethical standards. </li> </ul> <p>The annual base salary range is $125,000-200,000 (USD). Actual compensation offered to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.</p> <p> </p>

<p><strong>JOB RESPONSIBILITIES </strong></p> <p>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.</p> <p>We are looking for exceptional students to join us as quantitative researcher interns for Fall 2025, Spring 2026 and Summer 2026. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact.</p> <p>You will gain exposure to a variety of activities, which may include:</p> <ul> <li>Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application.</li> <li>Adapting and extending existing results in the broad field of machine learning; conducting novel research as needed to potentially develop new signals that may enhance portfolio returns.</li> <li>Analyzing very large data sets to extract features useful for predictive models.</li> <li>Providing research assistance to the team.</li> <li>Helping improve the team’s research infrastructure.</li> </ul> <p><strong>DESIRABLE CANDIDATES</strong></p> <ul> <li>Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines.</li> <li>Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets.</li> <li>Strong analytical and quantitative skills, and detail-oriented mindset.</li> <li>Proficient in Python or C++, and Linux environment.</li> <li>Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment.</li> <li>Willing to take ownership of his/her work, working both independently and within a collaborative team.</li> <li>Prior experience in the financial services industry is not required.</li> <li>Commitment to the highest ethical standards.</li> </ul> <p>The annual base salary range is $120000.00-$180000.00 (USD). Actual compensation offered to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.</p>

<p><strong><u>About Cubist</u></strong></p> <p>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.</p> <p><strong><u>Role/Responsibilities:</u></strong></p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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. </p> <p><strong><u>Requirements: </u></strong></p> <ul> <li>PhD or PhD candidate in machine learning, computer science, statistics, or a related field</li> <li>Experience with sequential modeling and time series forecasting using deep learning</li> <li>Experience with deep neural networks and representation learning</li> <li>Prior experience working in a data driven research environment</li> <li>Experience with translating mathematical models and algorithms into code</li> <li>Proficient in programming languages such as Python and R</li> <li>Experience with machine learning software libraries such as TensorFlow or PyTorch</li> <li>Experience with natural language processing technology a strong plus</li> <li>Excellent analytical skills, with strong attention to

<div class="slds-p-around_small slds-col slds-size_12-of-12" data-aura-rendered-by="555:596;a"> </div> <div class="slds-p-around_small slds-col slds-size_12-of-12" data-aura-rendered-by="563:596;a"><strong>JOB DESCRIPTION </strong> <div class="slds-form-element__control"> <p>This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading.</p> <strong>JOB RESPONSIBILITIES</strong> <ul> <li>Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies</li> <li>Identify features and relationships useful for the predictive modeling of market dynamics</li> </ul> </div> <div class="slds-form-element__control"> </div> <div class="slds-form-element__control"><strong>DESIRABLE CANDIDATES</strong><br> <ul> <li>MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline</li> <li>Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl</li> <li>Strong analytical and quantitative skills</li> <li>Demonstrated interest in financial markets and systematic trading</li> <li>Clear, concise, and proactive communicator</li> <li>Detail-oriented</li> <li>Willing to take ownership of his/her work, working both independently and within a small team</li> </ul> </div> </div>

<p> </p> <h3>About Cubist</h3> <p>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.</p> <h3>Role</h3> <p>Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies.</p> <h3>Job Description</h3> <ul> <li>Develop systematic trading models across FX, commodities, fixed income, and equity markets</li> <li>Alpha idea generation, backtesting, and implementation</li> <li>Assist in building, maintenance, and continual improvement of production and trading environments</li> <li>Evaluate new datasets for alpha potential</li> <li>Improve existing strategies and portfolio optimization</li> <li>Execution monitoring</li> <li>Be a core contributor to growing the investment process and research infrastructure of the team</li> </ul> <h3>Desirable Candidates</h3> <ul> <li>Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus</li> <li>Experience in quantitative trading, ideally in FX or futures</li> <li>Experience with alpha research, portfolio construction and optimization</li> <li>Experience building statistical/technical, fundamental, and data driven signals</li> <li>Experience synthesizing predictive signals for both cross-sectional and time-series models</li> <li>Strong experience with data exploration, dimension reduction, and feature engineering</li> <li>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</li> <li>Experience managing and running risk is a strong plus</li> <li>Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc.</li> <li>Creative mindset</li> <li>Strong time management ability—the ability to manage multiple tasks and deadlines in a fast-paced environment</li> <li>High degree of drive and energy—must be a self-starter</li> <li>Ability to work cooperatively with all levels of staff and to thrive in a team-oriented environment</li> <li>Commitment to the highest ethical standards and who act with professionalism and integrity at all times</li> </ul> <p><br>The an

<p><strong>ROLE/RESPONSIBILTIES: </strong></p> <p>We are seeking a quant research intern to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing.</p> <p>The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading.</p> <p>Responsibilities may include:</p> <ul> <li>Using NLP to construct features from varied datasets</li> <li>Formulating research hypotheses to derive alpha</li> <li>Building and testing the performance of trading signals based on NLP and financial features</li> <li>Launching identified signals into production</li> </ul> <p><strong>REQUIREMENTS:</strong></p> <ul> <li>Bachelor’s, Master’s or PhD candidate in computer science or other quantitative discipline</li> <li>Proficient in Python and general software engineering principles (github, testing, dev workflow)</li> <li>Strong understanding of machine learning and statistics</li> <li>Prior research experience preferred</li> <li>Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred</li> <li>Data science stack familiarity preferred</li> <li>An interest in financial markets</li> <li>Great attitude</li> <li>A collaborative mindset</li> <li>Commitment to the highest ethical standards</li> </ul> <p><strong>ABOUT POINT72:</strong></p> <p>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 investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.</p>

<p><strong>ABOUT CUBIST</strong></p> <p>Cubist Systematic Strategies 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.</p> <p><strong>RESPONSIBILITIES</strong></p> <ul> <li>Perform rigorous applied research to discover systematic anomalies in equities markets</li> <li>Present actionable trading ideas and enhance existing strategies</li> <li>Identify short term opportunities in the high frequency/intraday space</li> <li>Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)</li> <li>Contribute towards the team’s research tooling and its efficiency</li> <li>Help establish a collaborative mindset and shared ownership</li> </ul> <p><strong>REQUIREMENTS</strong></p> <ul> <li>Bachelor’s degree or higher in mathematics, statistics, computer science, or similar quantitative discipline</li> <li>3+ years of work experience in systematic alpha research in equities using high frequency/intraday data</li> <li>Fluency in data science practices, e.g., feature engineering, signal combining</li> <li>Technically comfortable handling large datasets</li> <li>Comfortable coding in both C++ and Python in a Linux environment</li> <li>Exposure working with cloud computing platforms such as AWS</li> <li>Highly motivated and willing to take ownership of his/her work</li> <li>Collaborative mindset with strong independent research ability</li> <li>Commitment to the highest ethical standards</li> </ul> <p> </p>

<p><strong><u>About the Team:</u></strong></p> <p>A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.</p> <p><strong><u>Role/Responsibilities:</u></strong></p> <ul> <li>Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals</li> <li>Perform feature engineering with order book tick data at intraday to daily horizons</li> <li>Perform feature combination using various modeling techniques ranging from linear to machine learning models</li> <li>Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation</li> <li>Help drive the growth of the investment process and research capabilities of the team</li> <li>Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets</li> <li>Assist in building, maintenance, and continual improvement of production and trading environments</li> </ul> <p><strong><u>Requirements: </u></strong></p> <ul> <li>MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics</li> <li>4+ years of experience in quantitative research, building statistical models for intraday to daily trading, as part of a successful proprietary trading team with a track record</li> <li>Knowledge of market microstructure for futures and/or FX</li> <li>Prior experience with tick data based feature generation, modelling, and monetization</li> <li>Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas</li> <li>Collaborative mindset with strong independent research abilities</li> <li>Commitment to the highest ethical standards</li> </ul> <p> </p>

<p><strong><u>About the Team:</u></strong></p> <p>A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.</p> <p><strong><u>Role:</u></strong></p> <ul> <li>Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets</li> <li>Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space</li> <li>Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation</li> <li>Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets</li> </ul> <p><strong><u>Responsibilities:</u></strong></p> <ul> <li>Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets</li> <li>Alpha idea generation, backtesting, and implementation</li> <li>Evaluate new datasets for alpha potential</li> <li>Contribute to and enhance portfolio optimization, allocation and risk management processes</li> <li>Help drive the growth of the investment process and research capabilities of the team</li> <li>Assist in building, maintenance, and continual improvement of production and trading environments</li> </ul> <p><strong><u>Requirements: </u></strong></p> <ul> <li>MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics</li> <li>4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record</li> <li>Prior professional experience with signal combination, portfolio optimization and risk management</li> <li>Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas</li> <li>Collaborative mindset with strong independent research abilities</li> <li>Commitment to the highest ethical standards</li> </ul> <p> </p>

<p><strong>JOB DESCRIPTION</strong></p> <p></p> <p>Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation.</p> <p>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.</p> <p><strong>DESIRABLE CANDIDATES</strong></p> <p></p> <ul> <li>Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field.</li> <li>Superb analytical and quantitative skills, along with a healthy streak of creativity.</li> <li>Demonstrated ability to conduct independent research utilizing large data sets.</li> <li>Passion for seeing research through from initial conception to eventual application.</li> <li>Curiosity about financial markets</li> <li>Strong scientific programming in Python, R or Matlab.</li> <li>Empirical, detail-oriented mindset.</li> <li>Sense of ownership of his/her work, working well both independently and within a small collaborative team.</li> </ul> <p>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 you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we’d love to learn more about what excites you.</p>

<p><strong>ABOUT CANVAS</strong></p> <p>On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research.</p> <p>Canvas is the supply chain research group within Market Intelligence. Canvas conducts compliant supply chain research by developing deep industry expertise, talking with private company executives, and synthesizing information for portfolio managers and analysts – our team produces impactful research that will change the way you look at the world.</p> <p><strong>ROLE SUMMARY</strong></p> <p>When you join the Canvas team, you’re signing up for the learning experience of your life. You will never look at anything the same – from grocery stores to tires to semiconductors. Every day you will speak with some of the most successful private company executives and learn about the businesses they’ve spent their lives building. You will synthesize your findings in comprehensive reports that are consumed by our investment professionals.</p> <p>Other Market Intelligence divisions do quantitative research to explain <em>what</em> is going on in an industry. As a Fundamental Researcher, your qualitative research will explain the <em>why.</em> In this role you will:</p> <ul> <li>Become a subject matter expert on an assigned industry</li> <li>Learn from small, medium, and large private company executives about their businesses and the industries in which they operate, including gathering qualitative data on what is happening (e.g., structural shifts; real-time changes in supply/demand dynamics; and emerging competitors, markets, and technologies) and, importantly, <em>why</em> it is happening</li> <li>Synthesize your findings in comprehensive reports that present a view of the industry</li> <li>Gain unparalleled exposure to, and learn from, business leaders across industries, including private company executives and your colleagues</li> <li>Interact directly with our investment professionals and learn the discretionary investment process to help drive more informed investment decisions</li> </ul> <p><strong>WHAT EXCITES YOU</strong></p> <ul> <li>Staying current on the evolving alternative data market and its role in discretionary investing</li> <li>Speaking with experts both inside and outside the Firm to understand data needs and offerings</li> <li>Analytical thinking and sifting through available data to find “the answer”</li> <li>Fast-paced work environments that at times require switching gears to address the needs of the business</li> <li>Working as

<p><strong>ABOUT PROPRIETARY RESEARCH</strong></p> <p>On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions posed by our investment professionals. We look for other bright, motivated, and collaborative people to join our team and grow with us—more than 90% of the leaders in our group were promoted from within.</p> <p><strong>ROLE SUMMARY</strong></p> <p>Our Data Scientists conduct research through data mining and statistical modeling to discover insights from big data that are used by our investment professionals to make investment decisions. You will have the opportunity to work in a highly collegial environment that emphasizes teaching and learning as a team. In this role, you will:</p> <ul> <li>Tackle the challenges of featuring and modeling large unstructured data using machine learning and statistical techniques</li> <li>Manage all aspects of the research and analysis process including methodology selection, data collection and quality, modeling and analysis, and performance monitoring</li> <li>Deliver research findings to investment teams, portfolio managers, and other internal clients</li> <li>Work within a team to help drive technical innovation through a collaborative R&D process</li> </ul> <p><strong>WHAT EXCITES YOU</strong></p> <ul> <li>Staying current on the evolving alternative data market and its role in discretionary investing</li> <li>Speaking with experts both inside and outside the Firm to understand data needs and offerings</li> <li>Multi-tasking and switching gears frequently to address the needs of the business</li> <li>Analytical thinking and ability to sift through large unstructured data sets</li> <li>Working in a fast-paced, dynamic environment</li> <li>Working as part of a cross-functional team made up of investment, research, and compliance professionals</li> <li>Experiment-based approach with freedom to innovate</li> </ul> <p><strong>WHAT EXCITES US</strong></p> <ul> <li>Excellent attention to detail, organization, and project management skills</li> <li>Strong verbal and written communication skills</li> <li>Superb business intuition and a solution orientated, methodological approach to problem solving</li> <li>

<p><strong>ROLE/RESPONSIBILITES</strong></p> <p></p> <ul> <li>Perform rigorous and innovative research to discover systematic anomalies in equity market</li> <li>End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization and production implementation</li> <li>Identify and evaluate new datasets for stock return predictions</li> <li>Maintain and improve the portfolio trading in production environment</li> </ul> <p><strong>REQUIREMENTS</strong></p> <p><strong></strong></p> <ul> <li>MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics</li> <li>1+ years of work experience in systematic alpha research in equities</li> <li>Experience developing short term alpha signals (intraday or a few days) is a plus</li> <li>Demonstrated proficiency in R or Python</li> <li>Strong command of foundations of applied statistics, linear algebra, and time series models</li> <li>Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources</li> <li>Strong knowledge of financial markets</li> <li>Highly motivated, willing to take ownership of his/her work</li> <li>Collaborative mindset with strong independent research ability<strong></strong></li> </ul>

<p><strong>ABOUT PROPRIETARY RESEARCH</strong></p> <p>On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research.</p> <p>Canvas is the supply chain research group within Market Intelligence. Canvas conducts compliant supply chain research by developing deep industry expertise, talking with private company executives, and synthesizing information for portfolio managers and analysts. Our team produces impactful research that will change the way you look at the world.</p> <p><strong>WHAT YOU'LL DO<br></strong>This 6-month intensive fellowship offers hands-on experience in research, business analysis, cross-functional collaboration, and the investment process within a fast-paced, compliance-focused environment. Canvas Fellows will be considered for permanent placement on the team following completion of the program.</p> <p>When you join the Canvas team, you’re signing up for the learning experience of a lifetime. You will never look at anything the same way—from grocery stores to tires to semiconductors. Every day, Canvas team members speak with private company executives and learn about the businesses they’ve spent their lives building. The team synthesizes findings in comprehensive reports that are consumed by Point72 investment professionals.</p> <p>Other Market Intelligence divisions do quantitative research to explain <em>what</em> is going on in an industry. As a Fundamental Researcher, your qualitative research will explain the <em>why.</em> During the 6-month program based in our New York office, you will:</p> <ul> <li>Become a subject matter expert on an assigned industry</li> <li>Engage with small, medium, and large private company executives about their businesses and the industries in which they operate, gathering qualitative data on key development—including structural shifts, real-time changes in supply/demand dynamics, and emerging competitors, markets, and technologies—with a focus on understanding <em>why</em> they are happening</li> <li>Synthesize your findings in comprehensive reports that present a view of the industry</li> <li>Gain unparalleled exposure to, and learn from, business leaders across industries, including private company executives and your colleagues</li> <li>Interact directly with our investment professionals and learn the discretionary investment process to help drive more informed investment decisions</li> <li>Partner on the above with dedicated Compliance professionals</li> </ul> <p><strong>WHAT EXCITES YOU</strong></p> <ul> <li>Staying current on the e

<p><strong>ABOUT CUBIST</strong></p> <p>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.</p> <p><strong>JOB DESCRIPTION</strong></p> <p>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.</p> <p>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.</p> <p><strong>DESIRABLE CANDIDATES</strong></p> <ul> <li>MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline</li> <li>3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX</li> <li>Strong analytical and quantitative skills</li> <li>Demonstrated ability to conduct independent research utilizing large data sets</li> <li>Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl</li> <li>Detail-oriented</li> <li>Willing to take ownership of his/her work, working both independently and within a small team</li> </ul> <p>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 you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we’d love to learn more about what excites you.</p>

<p><strong>ABOUT PROPRIETARY RESEARCH</strong></p> <p>On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions posed by our investment professionals. We look for other bright, motivated, and collaborative people to join our team and grow with us—more than 90% of the leaders in our group were promoted from within.</p> <p><strong>ROLE SUMMARY</strong></p> <p>Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly, extract insights from large, complex compliance approved structured and unstructured data sets. As a member of our Data Engineering team, you will work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will:</p> <ul> <li>Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery</li> <li>Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers</li> <li>Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies</li> <li>Build and support visualization and exploration capabilities around our big data sets</li> </ul> <p><strong>WHAT EXCITES YOU</strong></p> <ul> <li>Transforming large unstructured, data sets into valuable investment research inputs</li> <li>Learning and working with industry-leading cloud-computing technologies</li> <li>Speaking with experts both inside and outside the Firm to understand data needs and offerings</li> <li>Fast-paced work environments that at times require switching gears to address the needs of the business</li> <li>Working as part of a cross-functional team made up of investment, research, and compliance professionals</li> </ul> <p><strong>WHAT EXCITES US</strong></p> <ul> <li>Excellent attention to detail, organization, and project management skills</li> <li>Superb business intuition and a solution orientated, methodological approach to problem solving</li> <