Data Scientist

About Pearl

Founded in 2013, Pearl is a ratings and standards company building the national standard for home performance. Pearl SCORE™ rates every single-family home in the U.S. across five key pillars — Safety, Comfort, Operations, Resilience, and Energy — so homebuyers, homeowners, and real estate professionals can understand how a home performs in daily life.

Today, the value of a home is judged by its location, size, and aesthetics— but these factors overlook the home’s most important function: safeguarding the comfort, well-being, and finances of the people inside. Most American homes underperform in these regards because home performance is simply not on our radar. We can’t see it, quantify it, or put a value on it. Pearl aims to change that by making home performance a central part of how we view and value our homes.

We are not a home inspector, a contractor, a real estate platform, or a green-certification program — we rate homes against a transparent, evidence-based standard so that home performance becomes visible, measurable, and valuable in the real estate market.

As a Certified B Corporation, we're accountable not only to our shareholders, but also to the homeowners and communities we serve. For more information, visit pearlscore.com.

About the role

Pearl is seeking a Data Scientist to lead advanced research and predictive modeling, focusing on analyzing residential housing and energy performance data. The role involves utilizing causal inference and anomaly detection techniques to improve the accuracy of Pearl’s proprietary SCORE models and developing new performance metrics. Additionally, this position acts as the primary technical liaison for external research partners and contributes to the dissemination of findings through white papers and publications

What you'll do

* Manage research, conducted in partnership with external consultants and statistical firms, that identifies correlations and causal rel