Job Description

Compensation: $150,000$300,000 + equity + benefits

About Leo

At Leo, were 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

Were hiring an AI Researcher to push the frontiers of agentic decision systems. Youll 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 Youll 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

Youll be creating the quantitative core of Leos 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 level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Marketing Services

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