Quantitative Analysts

Quantitative Analysts (Quants) develop mathematical models for pricing, trading, and risk management in financial markets. They apply advanced mathematics, statistics, and programming to analyze market data, build trading algorithms, and help financial institutions make data-driven investment decisions. These professionals work primarily at investment banks, hedge funds, asset managers, and proprietary trading firms. The work is highly technical, combining finance domain knowledge with serious mathematical and programming skills. Quants often specialize in areas like derivatives pricing, algorithmic trading, or risk modeling. Quantitative Analysis offers exceptional compensation among the highest in any field, intellectually challenging work, and direct impact on trading outcomes. The role typically requires an advanced degree in a quantitative field. Career paths lead to senior quant roles, portfolio management, or founding quantitative trading firms.

Median Annual Pay

$200,000

Range: $120,000 - $450,000

Training Time

6-10 years

AI Resilience

🟡AI-Augmented

Education

Master's degree

📚Find Training Compare with other careers Calculate lifetime earnings

🤖AI Resilience Assessment

AI Resilience Score

Quantitative Analysts have moderate AI exposure as ML models increasingly automate pattern recognition and basic modeling tasks. However, developing novel trading strategies, understanding market microstructure, and making risk decisions requires deep expertise and creativity. AI becomes a powerful tool that quants leverage rather than a replacement. Growth of 20% reflects continued demand for quantitative approaches in finance.

🟡AI-Augmented

How we calculated this:

AI Exposure

Medium+1

40% of tasks can be accelerated by AI

Job Growth

Growing+1

+20% projected (2024-2034)

Human Advantage

High+2

EPOCH score: 14/25

Total Score4/6

Methodology: v2.0 - GPTs are GPTs / BLS / EPOCH Additive ScoringUpdated:

View full methodology →

📋Key Responsibilities

•Develop mathematical models for pricing derivatives and financial instruments
•Build and backtest algorithmic trading strategies
•Analyze market data to identify patterns and opportunities
•Implement risk models and stress testing frameworks
•Optimize portfolio construction and asset allocation
•Collaborate with traders and portfolio managers on strategy
•Research and implement machine learning techniques for finance
•Validate and maintain production trading systems

📈Career Progression

What does this mean?

This shows how earnings typically grow with experience. Entry level represents starting salaries, while Expert shows top earners (90th percentile). Most workers reach mid-career earnings within 5-10 years. Figures are national averages and vary by location and employer.

Entry (10th %ile)

0-2 years experience

$120,000

$108,000 - $132,000

Early Career (25th %ile)

2-6 years experience

$160,000

$144,000 - $176,000

Mid-Career (Median)

5-15 years experience

$200,000

$180,000 - $220,000