Applied Scientist, Pricing

Opendoor

Confirmed live yesterday Low trust

Quick summary

Work type
On-site
Location
Salary
$156,800–$335,000 / yr
Posted
122 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $205k
This role $246k
$135k most similar roles pay here $356k

This role pays more than 75% of similar roles. Most pay $162,375–$247,718 — the shaded band above. At the midpoint, this role pays about $246k versus about $205k 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 31 open roles on FindRole.

Listed pay typically runs $156,800–$335,000 across 6 roles with salary data.

Most-posted roles

View all roles at Opendoor

At a glance

TL;DR · Applied Scientist, Pricing

As an Applied Scientist- Pricing, you will join a nimble team focused on solving complex quantitative problems within the valuation and pricing ecosystem. You will build structural models, develop optimizers, and create demand and conversion models using pre-listing and post-listing signals to improve decisions regarding pricing, resale strategy, and portfolio risk management. The role involves designing experiments to quantify price elasticity and translating ambiguous business problems into rigorous modeling approaches where structure is essential over black-box predictions. You will utilize Python to develop production-quality scientific code and may leverage Pyspark for distributed data processing. Key technical areas include causal inference, Bayesian modeling, demand forecasting, pricing science, and mathematical optimization. Your work addresses the high-stakes challenge of making impactful improvements in a low-margin business by balancing objectives like margin, conversion, and risk through advanced statistical and econometric techniques.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Build models to support pricing, resale strategy, and portfolio risk management.
  • Develop demand and conversion models using pre-listing and post-listing signals.
  • Design optimization frameworks that balance margin, conversion, and risk objectives.
  • Apply structural modeling, econometrics, and mathematical techniques to solve complex business problems.
  • Design experiments to quantify price elasticity and customer response.
  • Translate ambiguous business problems into rigorous modeling approaches using high-dimensional data.
  • Develop production-quality scientific code in Python to move models from prototype to production.
  • Partner with cross-functional teams to integrate models into systems that influence real-time decisions.

What we're looking for

  • Experience developing quantitative models for decision-making under uncertainty.
  • Proficiency in Python with the ability to implement production-quality scientific code.
  • Expertise in 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 data.
  • Advanced degree (MS or PhD preferred) in a quantitative field such as statistics, mathematics, economics, operations research, or computer science.
  • 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.
  • Familiarity with distributed data processing tools like Pyspark and experience with machine learning or LLMs.

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