{"absolute_url":"https://job-boards.greenhouse.io/mw-tech-grad/jobs/8636830002","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":6449408002,"location":{"name":"London/New York"},"metadata":null,"id":8636830002,"updated_at":"2026-09-17T13:11:59-04:00","requisition_id":"818","title":"Quant Research - Quant Associate Programme - 2027","company_name":"Marshall Wace - Graduate \u0026 Associate roles","first_published":"2026-08-26T07:01:37-04:00","language":"en","application_deadline":null,"content":"\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;Start Date: Flexible between January and September 2027\u0026lt;/strong\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;Location: London/ New York \u0026lt;/strong\u0026gt;(note we have significantly more opportunities available in London)\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;strong\u0026gt;\u0026lt;span data-contrast=\u0026quot;auto\u0026quot;\u0026gt;About the programme\u0026lt;/span\u0026gt;\u0026lt;/strong\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{}\u0026quot;\u0026gt;\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;span data-contrast=\u0026quot;none\u0026quot;\u0026gt;You will be working in a position designed for high-calibre, highly numerate individuals within our quantitative teams. We value free thinkers, and we have created a fast-paced and meritocratic environment where you will be encouraged to apply your own initiative and challenge conventional wisdom. You will be delivering on the research agenda, in addition to back testing/researching forecasts of asset returns on horizons of hours to years.\u0026lt;/span\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{\u0026amp;quot;134233117\u0026amp;quot;:false,\u0026amp;quot;134233118\u0026amp;quot;:false,\u0026amp;quot;335551550\u0026amp;quot;:1,\u0026amp;quot;335551620\u0026amp;quot;:1,\u0026amp;quot;335557856\u0026amp;quot;:16711422,\u0026amp;quot;335559738\u0026amp;quot;:0,\u0026amp;quot;335559739\u0026amp;quot;:240}\u0026quot;\u0026gt;\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;span data-contrast=\u0026quot;none\u0026quot;\u0026gt;\u0026amp;nbsp;We all share a tireless drive for innovation and participants tend to be one of the top students at their university.\u0026amp;nbsp;Previous\u0026amp;nbsp;associates are now involved in creating and optimising our signature systematic trading models.\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{\u0026amp;quot;134233117\u0026amp;quot;:false,\u0026amp;quot;134233118\u0026amp;quot;:false,\u0026amp;quot;335551550\u0026amp;quot;:1,\u0026amp;quot;335551620\u0026amp;quot;:1,\u0026amp;quot;335557856\u0026amp;quot;:16711422,\u0026amp;quot;335559738\u0026amp;quot;:0,\u0026amp;quot;335559739\u0026amp;quot;:240}\u0026quot;\u0026gt;\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;span data-contrast=\u0026quot;none\u0026quot;\u0026gt;\u0026amp;nbsp;As a member of our Quantitative Associate\u0026amp;nbsp;Programme\u0026amp;nbsp;you will be part of a select cohort receiving on the job training from experienced colleagues who have a matchless record of helping high performing individuals reach their true potential.\u0026lt;/span\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{\u0026amp;quot;134233117\u0026amp;quot;:false,\u0026amp;quot;134233118\u0026amp;quot;:false,\u0026amp;quot;335551550\u0026amp;quot;:1,\u0026amp;quot;335551620\u0026amp;quot;:1,\u0026amp;quot;335557856\u0026amp;quot;:16711422,\u0026amp;quot;335559738\u0026amp;quot;:0,\u0026amp;quot;335559739\u0026amp;quot;:240}\u0026quot;\u0026gt;\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{\u0026amp;quot;134233117\u0026amp;quot;:false,\u0026amp;quot;134233118\u0026amp;quot;:false,\u0026amp;quot;335551550\u0026amp;quot;:1,\u0026amp;quot;335551620\u0026amp;quot;:1,\u0026amp;quot;335557856\u0026amp;quot;:16711422,\u0026amp;quot;335559738\u0026amp;quot;:0,\u0026amp;quot;335559739\u0026amp;quot;:240}\u0026quot;\u0026gt;\u0026lt;strong\u0026gt;\u0026lt;span class=\u0026quot;TextRun Underlined SCXW178625315 BCX8\u0026quot; lang=\u0026quot;EN-GB\u0026quot; data-contrast=\u0026quot;none\u0026quot;\u0026gt;\u0026lt;span class=\u0026quot;NormalTextRun SCXW178625315 BCX8\u0026quot;\u0026gt;Quant Research\u0026lt;/span\u0026gt;\u0026lt;/span\u0026gt;\u0026lt;/strong\u0026gt;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;You will research, develop, and refine the predictive signals and models that drive our investment strategies — turning data into alpha. The work spans statistical modelling, machine learning, large-scale data analysis, and signal research: sourcing and exploring novel datasets, designing and validating trading signals, rigorously backtesting hypotheses against real market conditions, and collaborating with portfolio managers to bring the strongest ideas into production. This is an intellectually demanding role where you will push the boundaries of what our models can capture and continually sharpen our competitive advantage.\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026amp;nbsp;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026amp;nbsp;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;What we look for:\u0026amp;nbsp;\u0026lt;/p\u0026gt;\n\u0026lt;ul\u0026gt;\n\u0026lt;li\u0026gt;Master\u0026#39;s degree or PhD in a highly quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, Engineering, or a related field\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Strong programming skills in Python, C++, or similar languages\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;A solid foundation in statistics, probability, and numerical methods\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Genuine interest in financial markets and systematic trading\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Sharp problem-solving ability and a rigorous, analytical mindset\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;The ability to work under pressure and manage competing priorities in a fast-paced, live trading environment\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;Clear communication skills - you can explain complex technical concepts to a range of audiences\u0026lt;/li\u0026gt;\n\u0026lt;li\u0026gt;A proactive, self-starter attitude with the drive to take ownership of projects from day one\u0026lt;/li\u0026gt;\n\u0026lt;/ul\u0026gt;\n\u0026lt;p\u0026gt;\u0026amp;nbsp;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;span data-ccp-props=\u0026quot;{\u0026amp;quot;134233117\u0026amp;quot;:true,\u0026amp;quot;134233118\u0026amp;quot;:true,\u0026amp;quot;201341983\u0026amp;quot;:0,\u0026amp;quot;335559740\u0026amp;quot;:240}\u0026quot;\u0026gt;Find out more here: \u0026lt;a href=\u0026quot;https://www.mwam.com/quantitative-associate-programme/\u0026quot;\u0026gt;https://www.mwam.com/quantitative-associate-programme/\u0026lt;/a\u0026gt;\u0026amp;nbsp;\u0026lt;/span\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;em\u0026gt;Marshall Wace is an equal opportunity employer. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other category protected by applicable law.\u0026lt;/em\u0026gt;\u0026lt;/p\u0026gt;\n\u0026lt;p\u0026gt;\u0026lt;em\u0026gt;In accordance with New York State and New York City pay transparency laws, the annual base salary for this position is $150,000 - $165,000. Actual compensation may vary based on factors such as experience, qualifications, and location. This role may also be eligible for a discretionary bonus and benefits.\u0026lt;/em\u0026gt;\u0026lt;/p\u0026gt;","departments":[{"id":4002431002,"name":"TOPS","child_ids":[4002437002,4002434002,4002436002,4002435002,4002438002],"parent_id":null}],"offices":[{"id":4058193002,"name":"London - Sloane Street","location":null,"child_ids":[],"parent_id":null}],"ai_disclaimer":null,"include_ai_disclaimer":null,"ai_opt_out_request_url":null}