Quant Research Postdoc Intern — Live Trading & Data

Citadel; Greenwich (CT); On-site; USD 205,000 - 264,000; Full time

Job summary

Citadel is offering an 11-week Quantitative Research internship designed to develop and test next-generation pricing models and trading strategies. You will work with senior researchers to translate complex statistical techniques into code and validate approaches on live data.

The internship runs June through August, with flexibility on timing. Collaboration, networking with peers, and exposure to a leading investment team are key features of the program.

Qualifications

• Post-doctoral degree in mathematics, statistics, physics, computer science, or another highly quantitative field.
• Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis, pattern recognition, NLP).
• Prior experience in a data-driven research environment.
• Experience translating mathematical models and algorithms into code (Python, R or C++).
• Independent research experience.

Responsibilities

• Conceptualize valuation strategies, develop and improve mathematical models.
• Back test and implement trading models and signals in a live trading environment.
• Use unconventional data sources to drive innovation.
• Conduct research and statistical analysis to build monetization systems for trading signals.

Skills

Quantitative background

Statistics

ML techniques

Time-series analysis

Python/R/C++

Independent research

Multi-tasking

Analytical skills

Communication skills

Education

Post-doctoral degree

Tools

Python

R

C++

Job description

Citadel is offering an 11-week Quantitative Research internship designed to develop and test next-generation pricing models and trading strategies. You will work with senior researchers to translate complex statistical techniques into code and validate approaches on live data.

The internship runs June through August, with flexibility on timing. Collaboration, networking with peers, and exposure to a leading investment team are key features of the program.