Junior Quantitative Researcher
Read straight from Scientech Research's careers page, verified 1d ago.Seekless can tailor your résumé to it.
Seekless can write your résumé for this posting first.
Before you apply
SalaryNo pay range posted
LocationNew Jersey
Work modeon-site
Typefull-time
SeniorityEntry
Experience1–3 yrs
DepartmentQuantitative Research
Company size51–200 people
PostedJan 23, 2025 · 1y ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on Jan 23, 202593% of this company's open roles have been listed for 90+ daysNo pay range listed, though New Jersey requires one
At a glanceSummarised by Seekless from the posting.
Advanced degree (master's or PhD) from a top university in science or engineering (Statistics, Mathematics, Computer Science, EE, or Physics preferred)
Formal training of independent academic research
1-3 years of work experience in systematic alpha research/equity trading
Proficient in C++ and Python
Good understanding of data science
Understanding of at least one of: statistical modeling, machine learning, econometrics, or optimization
Fast, critical, and reasonable thinking
Good communicator, rigorous, patient, and strong teamwork
Highly motivated, able to work in a fast-paced environment
Skills
C++
Python
Job Responsibilities:
1.
Support and improve existing trading strategies.
2.
Assist senior quantitative researchers to carry out quantitative strategy design, research and development in global futures, stock, options and cryptocurrency markets.
3.
Statistically analyze large-scale tick-by-tick financial data to extract alpha patterns.
Qualifications:
1.
Applicants must have graduated with advanced degrees from top universities, majoring in science and engineering, preferably Statistics, Mathematics, Computer Science, EE, and Physics. Have formal training of independent academic research.
2.
1-3 years of work experience in systematic alpha research/equity trading.
3.
Programming skills: proficient in the following programming languages - C++ and Python.
4.
Mathematical basics: having a good understanding of data science, being critical in learning knowledge, understanding at least one of statistical modeling, machine learning, econometrics or optimization.
5.
Being fast, critical and reasonable in thinking.
6.
Good communicator, being rigorous, patient, and having a strong sense of teamwork.
7.
Highly motivated, and able to work in a fast-paced environment.