Applied Scientist- Pricing

Opendoor

Quick summary

Work type: On-site
Location: Tempe, AZMiami, FL
Salary: $156,800–$335,000 / yr
Posted: 36 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $171k

This role $246k

$100k most similar roles pay here $360k

This role pays more than 88% of similar roles. Most pay $126,800–$215,375 — the shaded band above. At the midpoint, this role pays about $246k versus about $171k 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 36 open roles on FindRole.

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

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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 Miami, you will join the Research & Development team as a mid-level professional. Your primary responsibilities include developing and refining pricing models using advanced machine learning techniques, analyzing large datasets to optimize home valuation accuracy, and collaborating with cross-functional teams to integrate new features into existing systems. You will work extensively with Python, SQL, and TensorFlow, applying statistical analysis and predictive modeling skills to solve complex business challenges in the real estate market. This role requires a deep understanding of econometrics and data science principles, as well as experience in handling big data environments and cloud-based solutions like AWS or Azure.

Skills

Python SQL Machine Learning AWS CI/CD Git Scikit-learn Pandas NumPy TensorFlow Keras Docker Jupyter Notebook

What you'll do

Develop and implement advanced pricing models using machine learning techniques.
Analyze market trends and competitor strategies to optimize product pricing.
Conduct research on consumer behavior to enhance pricing algorithms.
Collaborate with data scientists to improve predictive analytics capabilities.
Evaluate the impact of pricing changes on revenue and customer satisfaction.

What we're looking for

PhD in Economics, Statistics, or a related quantitative field.
5+ years of experience in pricing strategy and economic modeling.
Strong expertise in machine learning and statistical analysis techniques.
Proven ability to develop and implement complex pricing algorithms.
Experience with data visualization tools and programming languages like Python/R.
Understanding of real estate markets and consumer behavior analytics.
Excellent communication skills for presenting findings to stakeholders.

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