Job description

Quantitative Researcher New Grad Job Description for Headlands Tech Locations: Amsterdam; Chicago; London; New York Scope : As a Quantitative Researcher at Headlands Tech, you'll join a team of quantitative researchers responsible for the firm's portfolio of automated electronic trading strategies. You'll research and develop predictive signals and trading models, iterating to drive measurable improvements in strategy PnL. Working closely with colleagues, you'll own ideas from hypothesis through production and be responsible for the results they generate. Qualifications : Low ego; effective both collaboratively and autonomously Highly motivated and ambitious, focused on real-world results Demonstrable interest in systematic trading; internship experience preferred Degree in a highly technical field (computer science, engineering, statistics, mathematics or physics) required Strong knowledge of statistics and machine learning with practical experience applying them to noisy real-world data Solid software development skills, with practical experience in Java, C++, or Python A drive to turn research into profitable, scalable, and maintainable strategies We are proud to be an equal opportunity workplace and to provide employees with a work environment free of discrimination and harassment. All employment decisions at Headlands Tech are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics. Headlands Tech will not tolerate discrimination or harassment based on any of these characteristics. By completing this application you agree to our GDPR and Privacy Policies .

Requirements

Must-haves

Quantitative Researcher New Grad Job Description for Headlands Tech
Locations: Amsterdam; Chicago; London; New York
Low ego; effective both collaboratively and autonomously
Highly motivated and ambitious, focused on real-world results
Degree in a highly technical field (computer science, engineering, statistics, mathematics or physics) required
Strong knowledge of statistics and machine learning with practical experience applying them to noisy real-world data
Solid software development skills, with practical experience in Java, C++, or Python
A drive to turn research into profitable, scalable, and maintainable strategies
By completing this application you agree to our GDPR and Privacy Policies .

Nice-to-haves

Demonstrable interest in systematic trading; internship experience preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningjavapython

Platform: greenhouse
Effort: quick