Machine Learning Researcher
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Before you apply
SalaryNo pay range posted
LocationNew Jersey
Work modeon-site
Typefull-time
SeniorityEntry
DepartmentQuantitative Research
Company size51–200 people
PostedMay 20, 2026 · 5mo ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on May 20, 202693% 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.
Bachelor’s degree or above from top domestic and international universities, majoring in Computer Science, Mathematics, Statistics, Machine Learning or related quantitative disciplines
Strong theoretical foundation in machine learning
Proficient in Python and mainstream deep learning frameworks
Capable of end-to-end data processing and independent modeling
Hands-on research or project experience in time series forecasting, NLP or other deep learning related domains
Logical, rigorous mindset with excellent self-learning capability and strong interest in applying ML to quantitative finance
Prior internship or working experience in Internet, AI, fintech or quantitative domains
Kaggle competition awards or first-author publications at top ML conferences (NeurIPS / ICML / ICLR)
Relevant internship experience in quantitative trading, asset management or financial technology
Skills
Python
deep learning frameworks
time series forecasting
NLP
machine learning
Responsibilities
Key Responsibilities：
1.
Mine alpha factors and build predictive models via deep learning based on multi-dimensional financial market data.
2.
Explore signal fusion and strategy ensemble approaches to enhance model robustness and portfolio return characteristics.
3.
Rapidly prototype, reproduce and optimize state-of-the-art deep learning models with mainstream ML frameworks.
4.
Stay updated on latest academic and industrial research, conduct ongoing model iteration and performance enhancement.
Requirements
Qualifications：
1.
Bachelor’s degree or above from top domestic and international universities, majoring in Computer Science, Mathematics, Statistics, Machine Learning or related quantitative disciplines.
2.
Strong theoretical foundation in machine learning, proficient in Python and mainstream deep learning frameworks; capable of end-to-end data processing and independent modeling.
3.
Hands-on research or project experience in time series forecasting, NLP or other deep learning related domains.
4.
Logical, rigorous mindset with excellent self-learning capability and strong interest in applying ML to quantitative finance.
5.
Prior internship or working experience in Internet, AI, fintech or quantitative domains.
Nice to have
Preferred Qualifications：
1.
Kaggle competition awards or first-author publications at top ML conferences (NeurIPS / ICML / ICLR).
2.
Relevant internship experience in quantitative trading, asset management or financial technology.