Junior Quantitative Researcher

Scientech Research LLC; Jersey City (NJ); On-site; USD 80,000 - 120,000; Full time

Job summary

A leading quantitative research firm in Jersey City seeks a motivated individual to support and improve trading strategies. The role involves assisting with quantitative strategy design, conducting analysis on large-scale financial data, and developing alpha patterns. Candidates must hold advanced degrees in relevant fields and possess strong programming skills in C/C++, Python, or R. The ideal candidate should thrive in a fast-paced environment and demonstrate outstanding communication and teamwork abilities.

Qualifications

• Graduated from a top university majoring in science or engineering.
• 1–3 years of experience in systematic alpha research or equity trading.
• Good understanding of data science and critical thinking skills.

Responsibilities

• Support and improve existing trading strategies.
• Assist in quantitative strategy design and research development.
• Analyze financial data to extract alpha patterns.

Skills

C/C++

Python

R

Statistical modeling

Machine learning

Data science

Education

Advanced degrees in Statistics, Mathematics, Computer Science, EE, or Physics

Job description

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 at least one of the following programming languages – C/C++, Python/R.
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從 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.