Deep Researcher at WorldQuant

Yerevan, Yerevan, Armenia

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Finance, Quantitative FinanceIndustries

Requirements

(None explicitly specified)

Responsibilities

Develop a structured and methodical research agenda combining fundamental knowledge, data exploration, and quantitative analysis
Become a domain expert on each fundamental topic covered, identifying key information drivers for research
Conduct detailed data exploration to acquire a comprehensive understanding of the data used to generate alphas
Enrich structured and unstructured data into datasets to enable quantitative research
Take a process-oriented approach to understand the value drivers of alphas

Skills

Quantitative Analysis

Data Exploration

Alpha Generation

Financial Strategies

Data Enrichment

Unstructured Data

Structured Data

Domain Expertise

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.

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