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Quantitative Researcher

Reposted 4 Days Ago
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Remote
Hiring Remotely in India
Entry level
Easy Apply
Remote
Hiring Remotely in India
Entry level
Quantitative Researchers at WorldQuant create models to predict financial market movements, leveraging rigorous data analysis and research methodologies.
The summary above was generated by AI

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models.

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Researcher. The person must have a strong understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges.

WHAT YOU’LL BRING:

  • Bachelor's (Hons), Master's or PhD degree in in a highly quantitative or highly analytical field e.g. Math, Physics, Computer Science or Financial Engineering from a leading university with excellent academic records are strongly preferred
  • Have a research scientist mindset, i.e., be a deep thinker, creative, persevering, smart, a self-starter, etc.
  • Knowledge of Linear Algebra, Statistics, Machine Learning
  • Prior experience in Finance/Trading is a plus.
  • Be competent in a programming language (Python, Unix)
  • Possess good English language skills
  • Have a strong interest in learning about worldwide financial markets
  • Possess a relentless drive to succeed, supplemented by a strong work ethic

By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.

Copyright © 2025 WorldQuant, LLC. All Rights Reserved.
WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

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