Machine Learning Researcher

Scientech Research LLC; New Jersey; On-site; USD 80,000 - 120,000; Full time

Job summary

Scientech Research LLC, located in New Jersey, is seeking candidates with a strong foundation in machine learning and quantitative finance. The role involves mining alpha factors and building predictive models using deep learning techniques. Candidates should hold a Bachelor's degree in Computer Science or related fields and be proficient in Python.

Ideal candidates will have hands-on experience in forecasting, excellent self-learning capabilities, and an interest in applying machine learning in finance. Preferred qualifications include awards in Kaggle competitions and experience in quantitative trading.

Qualifications

• Bachelor’s degree or above from top domestic and international universities.
• Proficient in Python and mainstream deep learning frameworks.
• Hands‑on experience in time series forecasting or NLP.

Responsibilities

• Mine alpha factors and build predictive models via deep learning.
• Explore signal fusion and strategy ensemble approaches.
• Rapidly prototype and optimize state-of-the-art deep learning models.

Skills

Machine Learning

Python

Deep Learning

Statistical Analysis

Education

Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field

Tools

Mainstream ML frameworks

Job description

Key Responsibilities

• Mine alpha factors and build predictive models via deep learning based on multi-dimensional financial market data.
• Explore signal fusion and strategy ensemble approaches to enhance model robustness and portfolio return characteristics.
• Rapidly prototype, reproduce and optimize state-of-the-art deep learning models with mainstream ML frameworks.
• Stay updated on latest academic and industrial research, conduct ongoing model iteration and performance enhancement.

Qualifications

• 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.

Preferred Qualifications

• 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.