Quantitative Research Engineer - PhD Graduate (US)
New Today
Compensation: $150,000–$300,000 + equity + benefits
Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out.
About Leo
At Leo, we’re building the platform that will 3x marketing ROI. Our AI agents handle the full lifecycle of digital advertising — from account audits and performance analysis to creative ideation, production, and media buying. By combining real-time data, advanced machine learning, and agentic intelligence, we deliver campaigns that consistently outperform traditional agencies at a fraction of the cost. Our ambition is clear: replace every ad agency in the world.
The Role
We’re hiring an AI Researcher to push the frontiers of agentic decision systems. You’ll design computational models that plan, simulate, and optimize at scale — models that evolve with feedback, adapt to markets, and improve continuously.
This is not a theory-on-paper role. The models you build will run in live production, influencing millions in ad spend, learning from outcomes, and delivering measurable performance. If you want to apply advanced quantitative methods in a fast-paced environment where rigor meets execution, this is the place to do it.
What You’ll Do
Build computational workflows that integrate statistical modeling, Bayesian inference, and Monte Carlo simulations
Design simulation environments so predictive systems can backtest, learn, and sharpen performance
Apply stochastic optimization, advanced quantitative methods, and machine learning to real marketing allocation problems
Connect your models directly to campaign planning, performance attribution, and automated decision engines
Run controlled experiments: validation, hypothesis testing, systematic parameter optimization
Translate research into production-ready systems that improve predictive accuracy and generate superior risk-adjusted returns over time
What You Bring
Ph.D. in a quantitative discipline (Mathematical Finance, Statistics, Mathematics, Physics, Computational Biology, Operations Research, Economics, Engineering, or related)
Strong quantitative modeling expertise with experience in computational methods and statistical inference
Experience with optimization algorithms, systematic backtesting, or computational modeling environments
Strong programming skills in Python, R, or C++ (and proven ability to engineer scalable prototypes)
A problem-solving mindset: the ability to move from mathematical theory → prototype → production quickly
Comfort working in a high-stakes, fast-moving, cross-functional environment where precision and speed both matter
Preferred Qualifications
Background in quantitative finance, algorithmic trading, or computational modeling
Experience with statistical software, numerical computing frameworks, or high-performance computing
Knowledge of time-series analysis, factor modeling, or risk management systems
Familiarity with backtesting methodologies, simulation frameworks, and performance evaluation metrics
Interest in applying cutting-edge quantitative research to systematic decision-making
Experience with distributed computing or real-time data processing pipelines
Why It Matters
You’ll be creating the quantitative core of Leo’s system . Every model you design will be used daily — by our team, our clients, and the system itself as it learns and adapts. This is applied quantitative research at scale: live, high-impact, and performance-driven.
Salary: $150,000–$300,000 per year + equity
Significant equity package with high growth potential
401(k)
Flexible PTO
Seniority level Seniority levelEntry level
Employment type Employment typeFull-time
Job function Job functionInformation Technology
IndustriesMarketing Services
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- Location:
- San Francisco, CA
- Salary:
- $200
- Category:
- Engineering
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