Applied Scientist- Pricing

Opendoor

Quick summary

Work type
On-site
Location
Tempe, AZSeattle, WA
Salary
$156,800–$335,000 / yr
Posted
33 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $177k
This role $246k
$110k most similar roles pay here $359k

This role pays more than 87% of similar roles. Most pay $137,979–$216,262 — the shaded band above. At the midpoint, this role pays about $246k versus about $177k 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 42 open roles on FindRole.

Listed pay typically runs $156,800–$335,000 across 8 roles with salary data.

Most-posted roles

View all roles at Opendoor

At a glance

TL;DR · Applied Scientist- Pricing

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As an Applied Scientist in Pricing at a leading tech company based in Seattle, you will join the Research & Development team as a mid-level professional. Your primary responsibilities include developing and refining pricing models that optimize revenue and customer satisfaction, working closely with data scientists and economists to analyze market trends and consumer behavior. You will build scalable machine learning systems using Python and R, leveraging cloud platforms like AWS for deployment. The role requires expertise in econometrics, statistical modeling, and experience with large datasets. Ideal candidates should have a strong background in quantitative analysis and be passionate about solving complex business problems related to real estate market dynamics.

Skills

Python SQL Machine Learning AWS CI/CD Scalability Performance Optimization Data Analysis Jupyter Notebook RStudio Git Docker Kubernetes PostgreSQL MLOps

What you'll do

  • Develop and implement advanced pricing models using machine learning techniques.
  • Analyze market trends and competitor strategies to inform pricing decisions.
  • Optimize algorithms to enhance accuracy and efficiency of price predictions.
  • Collaborate on research projects to innovate new approaches in real estate pricing.
  • Evaluate the impact of pricing changes on sales performance and customer satisfaction.

What we're looking for

  • 5+ years of experience in applied machine learning or related field.
  • Strong background in statistical modeling and data analysis techniques.
  • Proficiency in programming languages such as Python, R, or SQL.
  • Experience with cloud-based platforms like AWS, Azure, or GCP.
  • Excellent problem-solving skills and ability to innovate solutions.
  • Knowledge of pricing models and economic principles preferred.
  • Ability to work effectively in a collaborative team environment.

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