{"absolute_url":"https://boards.greenhouse.io/point72/jobs/8236734002?gh_jid=8236734002","data_compliance":[{"type":"gdpr","requires_consent":false,"requires_processing_consent":false,"requires_retention_consent":false,"retention_period":null,"demographic_data_consent_applies":false}],"education":"education_required","internal_job_id":6264325002,"location":{"name":"New York"},"metadata":[{"id":4076300002,"name":"Time Type","value":"Full Time","value_type":"single_select"}],"id":8236734002,"updated_at":"2026-10-01T15:44:08-04:00","requisition_id":"1980","title":"Micro-Intern: Research Technology Developer (IAP)","company_name":"Point72 ","first_published":"2025-10-31T12:02:59-04:00","language":"en","application_deadline":null,"content":"\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;\u0026lt;u\u0026gt;About Cubist\u0026lt;/u\u0026gt;\u0026lt;/strong\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;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.\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;\u0026lt;u\u0026gt;Job Description\u0026lt;/u\u0026gt;\u0026lt;/strong\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;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.\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;\u0026lt;u\u0026gt;Desirable Candidates\u0026lt;/u\u0026gt;\u0026lt;/strong\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;Undergraduate or graduate candidates in computer science or engineering\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Significant experience in Python and/or C++\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Interest in open source research tools for data science and machine learning\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Basic knowledge of linux, git, conda, and CI processes\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Knowledge of cloud, databases and distributed or streaming compute is a plus\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Reasonable quantitative and statistical skills\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Experience with Finance preferred\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Clear, concise, and proactive communicator\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Detail oriented and quick learner in a fast-paced environment\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Team player with strong pride of ownership\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Commitment to the highest ethical standards\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;","departments":[{"id":4077293002,"name":"Quant Management","child_ids":[4093681002,4093682002,4093683002,4093684002,4093685002,4127486002,4077294002],"parent_id":null}],"offices":[{"id":4007773002,"name":"New York, NY","location":"New York, New York, United States","child_ids":[],"parent_id":4041645002}],"ai_disclaimer":null,"include_ai_disclaimer":null,"ai_opt_out_request_url":null}