Quantitative Researcher: ML-Driven Investing

Two Sigma; New York (NY); On-site; USD 270,000 - 330,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

401k match

Life insurance

Disability insurance

Onsite gym

Wellness activities

Tuition/Conference sponsorship

Job summary

Two Sigma is a leading quantitative investment firm in New York seeking researchers to develop sophisticated investment models using rigorous scientific methods. You will apply machine learning to diverse datasets and collaborate with engineers to test theories.

You will join reading circles and attend seminars to learn from top researchers while sharing insights from conferences on statistics, machine learning, and data science.

Qualifications

• Degree in a technical or quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science (all levels welcome, from bachelor’s to doctorate)
• Intermediate skills in at least one programming language (like C, C++, Java, or Python)
• Experience performing an in-depth research project, examining real-world data
• Ability to think independently and creatively approach data analysis and communicate complex ideas clearly

Responsibilities

• Use a rigorous scientific method to develop sophisticated investment models and shape insights
• Apply quantitative techniques like machine learning to diverse datasets
• Create and test complex investment ideas and collaborate with engineers
• Join reading circles to stay updated on research papers and seminars from top universities
• Attend academic seminars to learn from thought leaders
• Share insights from conferences focused on statistics, ML, and data science

Skills

C/C++

Java

Python

Independent thinking

Education

Bachelor’s to Doctorate in quantitative fields

Job description

Two Sigma is a leading quantitative investment firm in New York seeking researchers to develop sophisticated investment models using rigorous scientific methods. You will apply machine learning to diverse datasets and collaborate with engineers to test theories.

You will join reading circles and attend seminars to learn from top researchers while sharing insights from conferences on statistics, machine learning, and data science.