ML Researcher for Quantitative Trading & AI

Citadel Securities; City of Rochester (NY); On-site; USD 235,000 - 300,000; Full time

Job summary

Citadel Securities is hiring a highly motivated quantitative researcher to advance ML/AI methods for modeling markets and guiding trading strategies. You will work with large datasets, including unstructured sources, and back-test models while documenting findings.

The role requires a PhD in a quantitative field, strong research credentials, and hands-on Python/C++ programming. A results-driven, detail-oriented mindset and the ability to communicate complex ideas succinctly are essential.

Qualifications

• PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field.
• Advanced training and strong research track record in statistics, machine learning, AI, or another highly quantitative field.
• Prior experience working in a data driven research environment. Detail oriented and can deep dive into the data.
• Hands on programming experience in scripting (e.g. Python) and/or compiled languages (e.g. C++)
• A background demonstrating strong problem-solving skills
• An ability to communicate advanced concepts in a concise and logical way
• Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems

Responsibilities

• Use statistics, machine learning or AI (e.g. deep learning, NLP) to extract patterns from various kinds of datasets through innovative and rigorous research
• Implement algorithms in high-quality code
• Work with large data sets, including unconventional and unstructured data sources
• Back-test models and document research findings

Skills

Statistics

Machine Learning

AI

Problem Solving

Communication

Algorithms

Education

PhD in quantitative field

Tools

Python

C++

Job description

Citadel Securities is hiring a highly motivated quantitative researcher to advance ML/AI methods for modeling markets and guiding trading strategies. You will work with large datasets, including unstructured sources, and back-test models while documenting findings.

The role requires a PhD in a quantitative field, strong research credentials, and hands-on Python/C++ programming. A results-driven, detail-oriented mindset and the ability to communicate complex ideas succinctly are essential.