Staff Data Scientist - Causality

Remote - San Francisco Bay Area /
Engineering – Data Science /
Full-time
About Opendoor:
Are you intrigued by the thought of disrupting a trillion dollar industry through technology? At Opendoor, we’re on a mission to make it simple to buy and sell homes. The traditional process is broken, with an average home taking over 90 days to sell and costing thousands of dollars. We empower everyone with the freedom to move by making buying and selling a home stress-free and instant. We’ve built an exceptional team, seen strong growth, served over 85,000 customers and recently went public! The coming years present a tremendous opportunity for innovation as we explore new frontiers and scale nationwide.

About the Role:
As a staff data scientist, you will lead the efforts to advance Opendoor’s ability to learn causes and effects. As a business focused on a small number of large transactions with a high degree of operational complexity, Opendoor cannot simply use rapid A/B testing as a way to establish cause-effect relationships for our strategic decisions. You will define and lead pragmatic causal learning practice at a company level using advanced experimentation, inference, and decision science techniques. You will identify limits of our current practices and continually incorporate state-of-the-art academia and industry, potentially drawing from non-obvious domains or applications. Moreover, you will have the technical command, business context and leadership stature to drive Data Science technical direction, cross-functional decision-making, and a culture of causal reasoning throughout the company.

As a Staff Data Scientist, you will:

    • Define and drive day-to-day causal learning practices across Opendoor business
    • Drive technical direction on advanced econometrics, causal inference, experimental design, etc. techniques across the Research & Data Science organization
    • Bridge cutting-edge academic and industrial research with the underlying shape of our strategic business questions to identify, synthesize and apply relevant insights.
    • Shape causal reasoning culture across Engineering, Product, Operations, Design, among other functions

We’re looking for teammates who have:

    • Advanced expertise in one of the following domains: causal inference, econometrics, experimental design, clinical trial, or any other fields where you’ve focused on establishing causality with dataInterests and proficiency working with fast evolving data sets around complex business
    • Strong strategic thinking and problem solving skills to apply academic knowledge on practical business questions
    • Strong communication and leadership skills to influence non-technical audiences with analytical insights
    • 7+ years of industry experience with advanced degree in a quantitative field
    • Programming sufficiency: SQL, Python/R, or any other of your preferred languages

Bonus Points:

    • You are excited to join a radically transparent team
    • You are committed to iteratively driving results
    • You are propelled forward by working on hard data science problems
    • You are interested in how to make the best decisions under uncertainty
More About Us
Want to learn more about us and how we are revolutionizing the home buying and selling process? Learn more about us on our website, check out our profile on The Muse to learn more about our culture from our team members, or read our blog posts to hear about the work we are doing.

We Offer the Following Benefits and Perks:
- Your choice of coverage for medical, dental, and vision (optional for dependents)
- Flexible vacation policy
- Commuter benefit
- Generous parental leave
- Paid time off to volunteer
Please note that these benefits and perks are available only to Full Time team members and do not apply to contract roles.

Opendoor values Openness
Our team celebrates our diverse backgrounds. We believe that being open about who we are and what we do allows us to be better. Individuals seeking employment at Opendoor are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, gender identity or other protected status under all applicable laws, regulations, and ordinances.