Sr. Data Scientist at Roofstock
Oakland, CA, US
Roofstock is the leading marketplace for investing in single-family rental homes that cash flow day one.  With over $1B in transactions, our mission is to make real estate investing radically accessible, cost effective and simple.  We want to use technology to transform the way real estate is bought and sold and make real estate investing as simple as investing in stocks.  Simply put, we are passionate about helping our customers build wealth through real estate.
 
Roofstock has been recognized as a great workplace by Glassdoor and Great Place to Work® and was recently named to the Forbes Fintech 50 and the Red Herring 100 lists of most innovative companies. Roofstock has raised $83M to date, is based in Oakland with approximately 180 people and is growing rapidly.  Check out our reviews and see why our employees love working here!
 
As a “full stack” data scientist you will write code that implements sophisticated models that solve business problems. You will work closely with product and other teams to solve challenges across the company in a high-visibility role. This is an excellent opportunity to join a small but quickly growing company that is leveraging novel data sets and machine learning to fundamentally transform the real estate investment space.

What You Will Do:

    • Build statistical, economic, and machine learning systems for:
    • Buyer segmentation & propensity modeling
    • NLP and image recognition & segmentation to extract signal from real estate listings
    • Property recommendation, matching, and personalization
    • Product experimentation
    • Time-to-buy survival analysis
    • Graph analysis of property ownership networks
    • Macroeconomic forecasting using ML
    • Modeling of capital expenses and operational costs like tenant churn
    • Work with large real-world structured and unstructured datasets
    • Learn and deploy new state-of-the-art data science tools
    • Carry out fundamental research and ship production models running on a modern cloud stack
    • Lead projects within cross-functional teams
    • Mentor junior colleagues and promote data/statistical literacy in the organization and beyond

What You Bring With You:

    • MS or PhD in statistics, computer science, economics, physical or social science, engineering, operations research, or similar quantitative and computational field
    • 2-4+ years of industry experience (4+ for MS) withadvanced statistical analysis/machine learning
    • Significant experience with one or more of: time series analysis and causal forecasting, monte carlo simulations, hierarchical modeling, propensity modeling, survival analysis
    • Proficient in R or python and their related data science ecosystems; advanced data carpentry skill
    • Engineering skills: you should enjoy writing well-documented robust code when needed; have solid knowledge of SQL; be comfortable with the command line and shell scripting.
    • Demonstrated ability to work independently, rapidly prototyping and testing new ideas
    • Experience evaluating the strengths and weaknesses of different modeling approaches
    • Demonstrated communication and collaboration skills to effectively present, explain, influence, and advise within cross-functional teams
    • Drive to solve problems, meet deadlines, and build whatever is necessary along the way

What We Offer:

    • An opportunity to be part of a well-funded mature start-up
    • Equity incentives to give you a stake in our future
    • Medical, Vision and Dental for you (95%) and your dependents (65%)
    • 401k
    • Pre-tax commuter benefits
    • Flexible Time Off and sick days
    • An upbeat and collaborative work culture
    • An attractive and inviting custom-designed office environment
    • A fully stocked kitchen with snacks and meals
    • Company-sponsored outings
    • Discounted Gym Memberships
Roofstock is an equal opportunity employer. In keeping with the values of Roofstock, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.