Quantitative Researcher – Entry-level PhD – Systematic Fund
Listed on 2026-02-28
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Finance & Banking
Data Scientist
Job title: PhD Quantitative Researcher (Cross-Asset)
Firm: Elite Quantitative Buy-Side Fund – Multidisciplinary team of academic researchers, finance industry experts and STEM subject matter experts.
Salary: Up to $200,000 starting base + exceptional bonus package.
Location: Chicago (Onsite)
This firm is a scientific and data-driven systematic fund who are currently at the forefront of systematic trading.
As a result of their stellar and continued success in the industry, they’re currently aggressively scaling their quantitative strategies business in Chicago. This is an invaluable opportunity to develop and implement systematic strategies alongside genuine experts in the field of quantitative trading.
Additional Information:
- Market leader within computational finance and systematic trading. Arguably one of the best industry performers of the last 3 decades.
- Renowned for developing quantitative strategies in systematic trading across an array of investment strategies and products (Equities, Futures, FI, Macro, Vol).
- Multidisciplinary team of exceptional subject matter STEM experts from finance, academia, and technology.
- Highly collaborative trading environment with data and execution managed centrally.
- Furthermore they're exploring and integrating fundamental/discretionary trading with data-driven quantitative trading.
Role:
- Explore and leverage an array of complex and noisy data (market, tick, options, alt) to identify statistical patterns and unique market opportunities.
- Contribute towards existing and novel strategies by refining methodologies and exchanging research ideas.
- Leverage sophisticated statistical methods to understand and manage risk, profitability and transaction costs in conceptualizing new trading ideas.
- Back-test and implement productionized trading models in a live trading environment.
- Contribute to the full lifecycle research strategy from data ingestion to alpha generation.
Required skills:
- Academic degree in mathematics, statistics, physics, computer science, or another highly quantitative discipline.
- Industry-related internship either within computational finance or technology. (Wil consider candidates with internships in other related data-driven fields).
- Knowledge of algorithms, data structures, probability and statistics.
- Experience of dealing with a multitude of noisy data challenges in a data-driven environment.
- Proficient in either C++ or Python.
- Experience with translating mathematical models and algorithms into code.
- Proficient in exploring and attaining value from noisy and complex data sets (alt, market, options, tick).
If this opportunity is of interest, please apply direct or email me directly at .
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