Quantitative Researcher, Systematic Equities & ML

Quant Blueprint LLC; Hong Kong; On-site; HKD 80,000 - 120,000; Full time

Job summary

Quant Blueprint LLC is looking for a Quantitative Researcher specializing in systematic equities. You will collaborate with the Senior Portfolio Manager to develop strategies grounded in data analytics and machine learning. The ideal candidate has over 3 years of experience in a trading environment and a strong background in data science tools and quantitative finance.

The role is based in Hong Kong but may also consider candidates from London or Dubai. Interested candidates should have a solid grasp of Python and experience with handling complex datasets.

Qualifications

• 3+ years of experience working in a systematic trading environment focused on equities.
• Experience with multiple vendor data sets: assessing, cleaning, and creating features.
• Demonstrated knowledge of machine learning concepts with hands-on experience.

Responsibilities

• Develop systematic trading strategies with a focus on idea generation and data analysis.
• Harness large financial datasets using statistical learning techniques.
• Implement machine learning frameworks and optimize code for scalability.

Skills

Proficient in modern data science tools (Jupyter, pandas, numpy, sklearn)

Expert in Python

Strong analytical skills

Experience with machine learning

Knowledge of quantitative finance

Education

Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field

Tools

KDB/Q

Job description

Quant Blueprint LLC is looking for a Quantitative Researcher specializing in systematic equities. You will collaborate with the Senior Portfolio Manager to develop strategies grounded in data analytics and machine learning. The ideal candidate has over 3 years of experience in a trading environment and a strong background in data science tools and quantitative finance.

The role is based in Hong Kong but may also consider candidates from London or Dubai. Interested candidates should have a solid grasp of Python and experience with handling complex datasets.