Applied Scientist - Pricing & Optimization

OpenDoor; Miami (FL); On-site; USD 156,800 - 335,000; Full time

Benefits offered by this job

Unlimited PTO

Health insurance

401(k)

Job summary

Opendoor is seeking an Applied Scientist to tackle quantitative challenges in pricing, resale strategy, and risk management. You will build models to inform decision making for pricing, inventory, and demand, and develop optimization systems that balance margins with risk.

The role emphasizes production‑quality code, cross‑functional collaboration, and hands‑on deployment. You will work on post‑listing demand, price elasticity estimation, experiments, and scalable optimizers.

Qualifications

• Experience developing quantitative models to support real‑world decision‑making under uncertainty.
• Strong coding skills in Python, with production‑quality code implementation.
• Experience with causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or optimization.
• Ability to translate messy real‑world data into rigorous modeling approaches.
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, OR operations research or related.
• Excellent communication and collaboration with cross‑functional teams.

Responsibilities

• Build models that help Opendoor make better decisions around pricing, resale strategy, and portfolio risk.
• Develop demand and conversion models using pre‑ and post‑listing signals.
• Design optimization frameworks balancing margins, conversion, and risk.
• Apply statistical and econometric techniques where structure matters.
• Design experiments to quantify price elasticity and product tradeoffs.
• Partner with Engineering, Product, and Operations to deploy models into production.
• Move quickly from idea to prototype to production‑readye scientific component.

Skills

Quantitative modeling

Python

Causal inference

Bayesian modeling

Structural modeling

Demand forecasting

Pricing science

Optimization

Communication

Cross-functional collaboration

Education

MS or PhD preferred in a quantitative field

Statistics or economics background

Tools

PySpark

SciPy/NumPy

Spark

Job description

Opendoor is seeking an Applied Scientist to tackle quantitative challenges in pricing, resale strategy, and risk management. You will build models to inform decision making for pricing, inventory, and demand, and develop optimization systems that balance margins with risk.

The role emphasizes production‑quality code, cross‑functional collaboration, and hands‑on deployment. You will work on post‑listing demand, price elasticity estimation, experiments, and scalable optimizers.