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Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Jun 27, 2023. WorldQuant scores B on the Alion truth index.

Overview
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Headquartered in Old Greenwich, Connecticut, WorldQuant is a global quantitative investment management firm and hedge fund. The company develops and deploys systematic trading strategies, predictive algorithmic signals ("alphas"), and data-driven portfolio management models across global equity and financial markets. By combining advanced machine learning, massive financial datasets, and a distributed international network of quantitative researchers, it systematically identifies market inefficiencies to generate consistent, risk-adjusted investment returns.

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: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing.

  • Perform analysis and generate models of financial datasets using machine learning techniques
  • Process, clean and verify the integrity of unstructured data and turn data into valuable insights
  • Develop and create data that seek to predict the movement of financial market
  • Transfer data into internal infrastructure applying variety of algorithmic techniques

What You’ll Bring:

  • Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas
  • Good academic record
  • Familiar with modeling, data structures, algorithms and optimizations
  • Strong knowledge of machine/deep learning algorithms
  • Proficient in programming languages of both C++ and Python
  • Possess good communication and presentation skills in English
  • Ability to work independently and as member of a team
  • Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart & a self-starter
  • Detail oriented and capable of multitasking and delivering in fast-paced work environment

As a plus:

  • While not mandatory, a strong interest in financial markets will definitely be beneficial
  • Participant of ACM-ICPC

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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