Quantitative AI Researcher
Impact: Trading alpha and risk-adjusted returns through expert quantitative AI research
Develop and apply machine learning and AI techniques to quantitative finance problems including algorithmic trading, risk modelling, portfolio optimisation, and market prediction. Conduct research, build and backtest models, and work with trading and risk teams to deploy AI-powered quantitative strategies.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 60% Team / 40% Solo
- Client facing
- Sometimes
- Impact visibility
- Moderate
- Travel
- 5 to 10% for industry events and academic conferences
- Schedule flexibility
- Moderate
- Remote work
- Hybrid
- Typical work hours
- 50 to 70 hours/week
- Stress level
- Low
At a glance
- Median salary
- $500,000
- Entry-level
- $200,000 - $300,000
- Senior
- $2,000,000+
- Growth by 2033
- 20% (faster than average)
- Demand
- Growing Fast
- Freelance potential
- Low
- Salary growth potential
- High - 65 to 80% growth from entry to senior
- Typical student debt
- Low
Skills you'll use
Hard skills
- 55
Soft skills
- 45
Technical complexity: Moderate
How to get there
- Minimum education
- PhD
- Licensing
- No
- Years to mid-career
- 3 to 5 years
- Years to senior
- 7 to 10 years
- Career switching
- Hard
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- Quantitative Analyst > Quantitative Researcher > Quantitative AI Researcher > Head of Quantitative Research > Chief Investment Officer
Future outlook
- Automation probability
- 10% very low risk as quantitative AI research requires deep expertise
- AI disruption risk
- Very Low
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 7/10
- Meaning
- 7/10
- Work-life balance
- 6.5/10
- Prestige
- 7/10
- Social perception
- High