AI Research Scientist (Value Addition) at WorldQuant

New York, New York, United States

Apply Now

Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Finance, Quantitative Finance, Investment ManagementIndustries

Requirements

Graduate-level calculus, linear algebra, optimization and machine learning algorithms knowledge
Graduate-level research experience in a quantitative field
Machine learning models research and operations experience
Experience working with “large” datasets (>100G CSV)
Excellent knowledge of Python, NumPy and Pandas
Experience with at least one of: XGBoost, LightGBM, CatBoost, Tensorflow, PyTorch, MOSEK, CVXPY
Experience with at least one of: Intel MKL, JAX, PySpark, Dask, Ray, ClickHouse, Vertica, Arrow
C++ knowledge is a plus
Passion for reasonable accuracy–explainability trade-offs in models
Willingness to explain and defend employed models, their interpretation and business value to the team and stakeholders
Ability to run full-length research work: from business idea, through data collection and model implementation, to tangible business data produced at regular frequencies
Experience in applying AI techniques to multi modal data and draw insights to support management decision making

Responsibilities

Build mathematical (optimization/machine learning/statistical) models for investment entity evaluation and resource allocation across them
Contribute code implementations and maintain existing code for evaluation models
Create on-demand analytical reports and produce business commentary on investment entities
Operate recurring entity evaluation pipelines

Skills

Quantitative Finance

Research

Data Analysis

Financial Modeling

Alpha Signals

Investment Strategies

Portfolio Management

Statistical Analysis

Programming

Machine Learning

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