below marketmost similar roles pay hereabove market
This role pays more than
79%
of similar roles. Most pay
$170,962–$241,789
— the blue band above.
At the midpoint, this role pays about
$246k
versus about
$206k
for comparable roles.
Based on 240 similar postings.
Employer
About Opendoor
Opendoor is a digital real estate marketplace that buys and sells homes directly to consumers, simplifying the home selling and buying experience through instant offers and transparent pricing. Industry: Real Estate Technology & iBuying
Opendoor currently has
21 open roles
on FindRole.
Listed pay typically runs
$156,800–$335,000
across 6 roles with salary data.
JOB TITLE: Applied Scientist- Pricing
The Applied Scientist- Pricing joins a small, nimble team to solve complex quantitative problems within a low-margin, high-stakes business environment. This role focuses on structural modeling, econometrics, optimization, and decision-making under uncertainty to influence pricing, resale strategy, demand modeling, and risk management. You will build demand and conversion models using pre-listing and post-listing signals, design optimization frameworks to balance margin and risk, and develop experiments to quantify price elasticity. Key requirements include an advanced degree in a quantitative discipline and proficiency in Python to implement production-quality scientific code. You will utilize causal inference, Bayesian modeling, and mathematical optimization to translate ambiguous business problems into rigorous models. Experience with Pyspark, machine learning, and marketplace modeling is also valued for this production-oriented role.
What does a Applied Scientist earn?
Median $208800 from 61 postings across 10 companies.
Build models to support decisions regarding pricing, resale strategy, and portfolio risk.
Develop demand and conversion models using pre-listing and post-listing signals.
Design and improve optimization frameworks to balance margin, conversion, and risk.
Apply statistical, econometric, and mathematical modeling techniques to problems requiring structural understanding.
Design experiments and measurement approaches to quantify price elasticity and customer response.
Implement production-quality scientific code in Python to move models from prototype to production.
Translate ambiguous business problems into rigorous modeling approaches using high-dimensional real-world data.
What we're looking for
Experience developing quantitative models to support real-world decision-making under uncertainty.
Strong coding skills in Python to implement production-quality scientific code.
Experience with causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization.
Ability to translate ambiguous business problems into rigorous modeling approaches using messy, high-dimensional real-world data.
Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline.
Strong communication and collaboration skills to convey technical ideas to cross-functional stakeholders.
Experience in pricing, marketplace modeling, revenue management, supply/demand systems, inventory optimization, or risk modeling (preferred).
Background in real estate, housing, finance, or adjacent marketplace domains (preferred).