Quantitative Researcher
CTC Trading Group, LLC · New York, NY telecommuting permitted
Experience must include
Strong mathematical background (Statistics, Probability, Linear Algebra)Independent research experience with Quantitative Modeling and Trading IntuitionC++PythonData literacy including big data technologiesStatistical libraries for data analysisAdvanced programming skillsSoftware development lifecycle
Apply
Only apply if you genuinely want this job and meet every stated requirement. RapidApply can check your profile against the requirements and prepare a truthful application packet for you to review — nothing is sent without your approval.
Check my fit & prepare an applicationWhere this job is advertised
Application instructions (verbatim)
Applicants who are interested in this position may apply at https://www.jobpostingtoday.com/ Ref # 48677
This source's terms don't allow us to republish the full ad; read it at the original posting. Signed-in applicants see the full text on their fit page.
Application instructions (verbatim)
Applicants who are interested in this position may apply at https://www.jobpostingtoday.com/ Ref # 48677
Full posting text
Quantitative Researcher CTC Trading Group, LLC — New York, NY CTC Trading Group, LLC seeks a Quantitative Researcher in New York, NY. Duties: Partner directly with trading to turn market observation and intuition into working hypotheses. Collaborate with trading and technology to build world class models that help us describe the ever-changing world around us. Assess the strength of both current models and new candidate models by using intuition, data, and first principles. Participate in a rapid innovation cycle that produces demonstrable wins through the feedback loop of quantitative research, trading,post-trade analysis, and iterative workflows. Conduct research and design experiments to improve existing strategies and deploy new strategies that monetize opportunities in a constantly evolving market environment. Build data-based tools and workflows to further systematize our approach to trading and risk management. Learn from an experienced team with a diverse knowledge base across trading, quant, and technology. Telecommuting Permitted. Requires a Masters degree in Statistics, Management Science, Machine Learning, Computer Science, Physics, or a related quantitative field, plus 9 months of related experience. Requires 9 months of experience in the following: Strong mathematical background (Statistics, Probability, Linear Algebra). Independent research experience with a proven track record of pairing Quantitative Modeling and Trading Intuition to solve complex problems. Expertise in C++ or Python. Data literacy including the ability to leverage big data technologies, work with different data storage systems and leverages statistical libraries for data analysis. Advanced programming skills and experience with the software development lifecycle. Alternatively, the employer will also accept a Bachelors degree in Statistics, Management Science, Machine Learning, Computer Science, Physics, or a related quantitative field plus 3 years of related experience. Requires 3 years of experience in the following: Strong mathematical background (Statistics, Probability, Linear Algebra). Independent research experience with a proven track record of pairing Quantitative Modeling and Trading Intuition to solve complex problems. Expertise in C++ or Python. Data literacy including the ability to leverage big data technologies, work with different data storage systems and leverages statistical libraries for data analysis. Advanced programming skills and experience with the software development lifecycle. 40 hours/week, Wage Range: $200,000-$250,000 per year. Must also have authority to work permanently in the U.S. Applicants who are interested in this position may apply at https://www.jobpostingtoday.com/ Ref # 48677
Why we think this is a PERM ad (100% confidence): Rules: PERM-form signals: offered_position_form, reference_code, telecommute, degree_field, exact_experience, form_like_headers