Research Scientist (QR) - Intraday Systematic Equities
A leading quantitative investment firm is seeking an exceptional Research Scientist to join a systematic equities team focused on developing predictive models and extracting insights from large, complex datasets. The role sits at the intersection of machine learning, statistics, and quantitative research, with a particular emphasis on intraday equity prediction and alpha discovery.
This position is designed for candidates who have excelled in the most rigorous academic and professional environments. We are specifically targeting quantitative researchers from top-tier universities and highly selective research-driven organizations where scientific rigor, innovation, and intellectual curiosity are core to the culture.
Responsibilities

• Conduct original alpha research using machine learning, statistical modeling, and data science techniques.
  
• Develop predictive models and novel alpha signals from structured and unstructured datasets.
• Design robust research frameworks and experimental methodologies.
• Partner closely with portfolio management to identify and validate investment opportunities.
• Maintain the highest standards of data quality, research hygiene, and model validation.

Qualifications

• 2-4 years of experience in quantitative research, machine learning research, or a closely related field.
• Exceptional academic credentials from a globally recognized top-tier university.
• Degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a similarly quantitative discipline.
• Experience at a leading quantitative hedge fund, proprietary trading firm, top technology company, or elite research organization.
• Strong programming skills, particularly in Python and data-intensive research workflows.
• Outstanding analytical, mathematical, and problem-solving abilities.

Ideal Candidate

• Research-first mindset with a genuine scientific approach to problem solving.
• Thoughtful and methodological rather than purely iterative.
• Deep appreciation for data quality, experimental design, and reproducible research.
• Experience applying machine learning to challenging real-world prediction problems.
• Track record of operating in highly selective academic and professional environments.
• Interest in systematic investing, market prediction, and large-scale data analysis.

Target Backgrounds
Candidates are most likely to come from leading quantitative investment firms, top proprietary trading firms, premier technology companies, or world-class research groups. Strong preference will be given to individuals with both elite academic pedigree and experience in exceptionally high-performing research environments.