Lead Data Scientist

Job Title: Lead Data Scientist

Location: Fully Remote

Compensation: $180,00 - $200,000, bonus, + equity

Role: Lead Data Scientist

A high-growth B2B SaaS company in hospitality is re-architecting its core pricing engine. The goal: replace static, rules-based logic with adaptive, self-learning RL systems that react to real-time demand signals, booking behavior, and market shifts. You’ll lead modeling efforts that directly influence pricing across thousands of locations, shaping millions in revenue annually.

Why This Role Matters

Pricing is the company’s crown jewel - and it’s being completely rebuilt. This is a rare opportunity to apply reinforcement learning in production, solving real business problems with measurable ROI. You’ll work with a greenfield mandate, strong MLOps support, and executive buy-in to make RL the backbone of a next-gen pricing engine.

What You’ll Do

• Architect and train reinforcement learning models (bandits, DDPG, PPO, etc.) for real-time pricing optimization
• Explore both model-based and model-free methods; experiment with policy gradients and value-based techniques
• Build offline simulation environments to safely evaluate pricing policies before live deployment
• Encode real-world constraints (e.g., price floors, caps, competitor pricing) into model architectures
• Partner with MLOps to deploy RL agents into production (e.g., AWS SageMaker, MLflow)
• Own the end-to-end experimentation stack: causal inference, uplift modeling, and A/B testing
• Collaborate tightly with product and engineering to influence roadmap and business strategy

Tech Stack

• Languages/Frameworks: Python, PyTorch, TensorFlow, SQL, scikit-learn
• Infra: AWS SageMaker, MLflow
• Modeling: RL simulators, custom optimization frameworks, demand elasticity models
• Deployment: Batch or real-time pricing APIs

Ideal Candidate

• Ample experience data science roles with deep experience in pricing, optimization, or control systems
• Hands-on with reinforcement learning in production: bandits, deep RL (DDPG, PPO, AlphaZero-style)
• Strong grasp of optimization theory and simulation modeling
• Enjoys working across disciplines - bridging data science, product, and infrastructure
• Thrives in greenfield environments where fast iteration and business impact are the norm

About Us

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