Applied Scientist, Pricing

Opendoor

Confirmed live 2 days ago Low trust

Quick summary

Work type
On-site
Location
Salary
$156,800–$335,000 / yr
Posted
122 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k
This role $246k
$135k most similar roles pay here $356k

This role pays more than 75% of similar roles. Most pay $164,375–$247,718 — the shaded 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 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 inform resale strategy and risk management. Your daily work involves translating ambiguous business problems into rigorous modeling approaches, designing experiments to quantify price elasticity, and developing production-quality scientific code. The role requires expertise in Python, with additional experience in causal inference, Bayesian modeling, demand forecasting, pricing science, or mathematical optimization. You will navigate high-dimensional data to solve challenges in a low-margin, high-stakes business environment. Preferred skills include familiarity with Pyspark, machine learning, and large language models to improve decision-making across products and inventory while balancing margin, conversion, and risk.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Build models to inform 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, production-ready scientific models.
  • Implement high-quality Python code to move models from prototype to production systems.

What we're looking for

  • Experience developing quantitative models for real-world 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 discipline like statistics, mathematics, economics, operations research, or computer science.
  • Strong communication and collaboration skills to convey technical ideas to cross-functional stakeholders.
  • Experience with pricing, marketplace modeling, revenue management, supply/demand systems, inventory optimization, or risk modeling.
  • Familiarity with distributed data processing tools such as Pyspark.

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