{"id":1636858,"url":"https://alion.io/job/radix-trading-quantitative-researcher-full-time-phd","title":"Quantitative Researcher (Full-Time - PhD+)","company":{"id":3854032,"name":"Radix Trading","domain":"radixtrading.com","url":"https://alion.io/company/radix-trading","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":116000,"max_usd":255000,"period":"year","method":"role_country_seniority_unknown","sample_n":3418},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2025-01-31T17:08:15Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-25T07:46:38Z","board_verified":true,"closed_at":null,"days_open":631,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":631},"description":"Please only apply to one of our Job Postings. At the bottom of the application questions below you'll have the option to indicate if there are any other roles here at Radix that you might be interested in. Please do not submit multiple applications for different positions. \nAs a Quantitative Researcher, your focus is on identifying trading opportunities, but you can add even more value with strong quantitative skills and some coding proficiency to accelerate the innovation process and help others leverage your work. \nBy working on a variety of projects with different collaborators over the start of your career, you’ll gain new knowledge and insight into the fundamentals of market dynamics, trading strategies, and our proprietary research platform. We believe in learning through impactful work, so while you learn the intricacies of our industry, you’ll have plenty of opportunities to contribute and directly affect our bottom line within your first few weeks on the team. \nWhile interest in trading is key, a background in finance is definitely not. Our team is built mostly from academia - not from other trading firms.We seek mental diversity and add a select group of academics each year from a wide range of disciplines. \nCOMPENSATION - Competitive salary, plus quarterly bonus based on individual performance and contribution towards success of others and the firm.\nQualifications\nWe’re looking for highly analytical people (math, physics, computer science, statistics, electrical engineering, etc.) who want to help build the research-driven trading firm of the future. To do that, you’ll need the following qualities:\nCurrently a PhD Student, Postdoc, Professor, or hold a similar advanced research position at a University\nPersistent Drive to Improve - Do you have an innate desire to rise to the next level, even after great accomplishment?\nCreative Problem Solving and Probabilistic Thinking - You must enjoy learning and implementing new concepts quickly, combining knowledge from different domains to create new ideas, and take a data-driven and probabilistic approach to testing and implementing new ideas.\nTeam Mindset - We want people who understand 1+1 > 2 and are as committed to making the team better through sharing ideas as they are driven to improve their individual performance.\nMental Flexibility & Self Awareness - You’ll have to frequently adapt based on new data, results, and feedback on your trading ideas and your performance.\nOrientation for Making Money - Although we value academic training, our work is not an academic exercise. We take a hacker’s approach to testing ideas, dropping projects that consume time without high upside, and focusing our next efforts on what will create the most value for the firm.\nResearch / Quant trading strategy skills to have or develop\nStrong intuition and deep thinking with data sets - Designs new alphas, understands complex systems; knows where to start, or ask others where to start\nDemonstrates strong “hacking” ability to quickly get into data to look for empirical relationships and decipher noise or signal\nFamiliarity with classical statistical methods and knows when and how to apply them in a rigorous fashion; Easily learns how to apply new statistical methods; will seek out and learn new methods to better solve problemExperience with modern AI techniques and methods or desire to work on Applied Machine Learning Problems a plus\n\nConstantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal\nExperience in setup of research framework and execution of projects\nUnderstanding of financial products, market dynamics, and microstructure\nExperience programming in Low-level computer languages (like C++); 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