**Lead Data Scientist (Reinforcement Learning)
$230,000 base + 10% bonus + equity
Remote (USA only)
No visa sponsorship or transfer**
We’re hiring multiple Lead Data Scientists to build production-grade pricing and reinforcement learning systems for a global AI-powered revenue optimization platform.
You’ll design and deploy models that dynamically adjust prices, learn from real-time behavior, and optimize long-term outcomes across a massive dataset of transactions and demand signals.
What you’ll do:
Develop dynamic pricing algorithms using reinforcement learning and contextual bandits
Model demand elasticity, price sensitivity, and uncertainty to guide strategic decisions
Create simulation and experimentation frameworks to evaluate pricing policies
Write production-quality Python code and collaborate with MLEs to deploy at scale
Partner with data, engineering, and product teams to turn complex models into live systems
What we’re looking for:
6+ years of applied ML or data science experience (pricing, optimization, or RL)
Strong Python engineering and ML deployment skills (AWS, MLflow, Airflow, etc.)
Hands-on experience with reinforcement learning, bandits, or decision optimization
Familiarity with statistical modeling, demand forecasting, or time series a plus
A collaborative and pragmatic problem solver who thrives on shipping real systems
Compensation:
Base salary up to $230,000
15% annual bonus
Significant equity potential via 3–5 year private equity exit plan
Fully remote within the US
If you’re passionate about designing intelligent systems that make pricing decisions in the real world — and enjoy owning projects end-to-end from model design to production — this is an opportunity to have an impact at scale.