Head of Data Science

At Divvy Homes, we're building an on-ramp to homeownership – one that's more flexible, more affordable, and an all-around better fit for today’s American family – and it’s working. Recognized as Time 100’s most influential companies of 2022 and a Great Place to Work, Divvy strives to build a team that can uphold our mission.

About This Role

We are looking to hire a senior leader to become our Head of Data and help use machine learning and analytics to scale both the volume and performance of our business. In this role, you'll oversee the Data Science and Analytics org, with responsibility for defining and executing on the roadmap, hiring and scaling the team, and leveraging modeling, experimentation, and analytics to impact our business strategy. Some examples of focus for the org include:

1. Asset Value Model - Our automated valuation model (DVM) is responsible for computing the offer price on both on-market and off-market homes, for use in new acquisitions as well as dispositions.
2. Credit Risk Model - Our proprietary risk model (RPM) is used to drive high efficiency underwriting decisions and manage towards a low default rate, offering 2x improvement over FICO for the most at risk groups.
3. DivvyAI - Our in-development product offering which leverages LLMs and inference to create a front-office property management agent that automates responses to inbound communications.
4. Experimentation - At any given time, we have a handful of active experiments running to better understand pricing elasticity, DOM reduction, and other levers critical to our business.

The ideal candidate will have a strong technical background, coupled with years of leadership experience. Your day to day will be a combination of team management, individual contribution, interfacing with other company leaders, and longer term planning. A proven history of hiring and retaining senior talent is strongly desired.

You will report to the co-founder/CTO and have regular exposure and interaction with the executive team, board, and investors. 

We have a documented equal pay policy, and do not negotiate on offers. To maintain fairness and keep starting total comp the same for anyone who comes into that position, individual pay is determined by role, level and work location only. At offer stage, we give candidates 3 different offers to choose from depending on how they want to favor cash vs equity. The US-based salary range for this position is $269,000 to $312,300 + equity + benefits. 

Responsibilities:

• Oversee the strategy, roadmap, and execution of the Data Science and Analytics organization
• Partner with other Divvy leaders to identify opportunities to improve business performance with modeling, experimentation, and analytics
• Contribute as an IC to our highest-impact models
• Oversee research and development of our risk models
• Oversee our analytic systems (Snowflake + Sigma)
• Influence Divvy’s product offerings based on quantitative insights
• Become a domain expert in real estate risk and pricing

Skills & Experience:

• 8+ years of experience in machine learning or data science, with at least 4 years of management experience
• A history of hiring and retaining senior talent
• Experience in either R or Python
• A strong understanding of statistical modeling and machine learning techniques
• You demonstrate the ability to clearly communicate analysis
• Bonus points for previous credit default modeling experience, risk management experience, and/or real estate pricing (AVM) experience
• Bonus points for executive or board level experience

#LI-Remote

Divvy Homes is committed to building a diverse and inclusive team. We are woman-led and have focused on diversity, equity and inclusion from the moment Divvy was founded. Divvy has 8 Employee Resource Groups (ERGs) to celebrate not only our cultural uniqueness, but also to create a sense of belonging. We care deeply about hiring a workforce that is diverse not only in gender and ethnicity, but in experience, thought, and geography. We enthusiastically encourage individuals from a variety of lived experiences to reach out and learn more about our roles at Divvy.