Quantitative Researcher at WorldQuant

Hanoi, Hanoi, Vietnam

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

FinanceIndustries

Requirements

PhD or M.S. degree from a leading university in a quantitative or highly analytical field (e.g., Electrical Engineering, Physics, Computer Science, Mathematics, Financial Engineering)
Ranked in the top 10% of bachelor’s degree class
Demonstrated ability to program in C/C++ on a Unix/Linux platform
Excellent problem-solving abilities and judgment with a strong attention to detail
Mature, thoughtful, with the ability to operate in a collaborative, team-oriented culture
Strong English language skills; ability to communicate complex concepts in simple terms
Possession of an international or regional Mathematical Olympiad medal is a plus

Responsibilities

Create computer-based models to predict movements of global financial markets
Employ tested processes to identify high-quality predictive signals (mathematical expressions of data)
Contribute to the development of quantitative models

Skills

Key technologies and capabilities for this role

C++CUnixLinuxMathematics

Questions & Answers

Common questions about this position

What compensation does WorldQuant offer for the Quantitative Researcher role?

WorldQuant offers a competitive and attractive compensation package with a clear career roadmap.

Is this Quantitative Researcher position remote or office-based?

This information is not specified in the job description.

What are the key requirements for the Quantitative Researcher position?

Candidates need a PhD or M.S. from a leading university in a quantitative field like Physics or Computer Science, top 10% academic ranking in bachelor's, and demonstrated C/C++ programming skills on Unix/Linux. Excellent problem-solving, communication in a team environment, and strong English skills are also required.

What is the company culture like at WorldQuant?

WorldQuant emphasizes a culture pairing academic sensibility with accountability for results, encouraging open thinking, intellectualism, continuous improvement, and collaboration in teams. They value intellectual horsepower and a drive for building future success.

What makes a strong candidate for the Quantitative Researcher role at WorldQuant?

Strong candidates have a PhD or M.S. from a top university in a quantitative field, top 10% bachelor's ranking, C/C++ programming expertise, exceptional problem-solving, and a Mathematical Olympiad medal is a plus. Prior finance experience is not required but interest in finance is essential.

WorldQuant

Quantitative asset management using algorithms

About WorldQuant

WorldQuant is a quantitative asset management firm that focuses on managing investments for institutional clients like pension funds and sovereign wealth funds. The firm uses data and predictive algorithms to analyze financial markets and identify investment opportunities. Its approach involves algorithmic trading, where mathematical models guide investment decisions. Unlike many competitors, WorldQuant encourages a culture of experimentation and innovation among its employees, allowing everyone to contribute ideas regardless of their position. The company's goal is to generate returns for its clients while maintaining a commitment to equal opportunity in the workplace.

Greenwich, ConnecticutHeadquarters

2007Year Founded

$148.5MTotal Funding

N/ACompany Stage

Quantitative Finance, Financial ServicesIndustries

1,001-5,000Employees

Benefits

Performance Bonus

Flexible Work Hours

Risks

Increased competition from AI-driven investment firms like ADIA.

Regulatory scrutiny on algorithmic trading practices is increasing globally.

Market volatility challenges the performance of algorithmic trading models.

Differentiation

WorldQuant employs over 1,000 professionals across 27 global offices.

The firm uses predictive algorithms to manage assets and generate client returns.

WorldQuant emphasizes equal opportunity, allowing all employees to contribute meaningfully.

Upsides

Increased focus on alternative data sources is gaining traction in quantitative finance.

Machine learning integration in portfolio management allows better market trend predictions.

Quantum computing offers potential for faster, complex calculations in algorithmic trading.

Land your dream remote job 3x faster with AI

Try Jobo Free