Orchard is radically simplifying the way people buy and sell their homes. For the average American, the home purchase and sale process takes months, creates anxiety, and is filled with uncertainty and hassle. Orchard has reimagined the end-to-end experience of buying and selling, from innovative home search tools to find the perfect home to the ability to buy a new home before selling your current one. Orchard customers manage the entire experience through a personalized online dashboard, while also getting the support of best-in-class Orchard real estate agents.
Headquartered in New York City and with offices throughout Texas, Colorado, Georgia, North Carolina, and Virginia, Orchard has over 400 employees and growing. We have raised over $130 million in equity financing from top-tier investors including Revolution, Firstmark, Accomplice, Navitas and Juxtapose. Our investors have also backed the likes of Pinterest, AirBnb, Shopify and Sweetgreen. Orchard is proud to be recognized as part of Glassdoor’s Best Places to Work.
About the Role and Team:
Orchard’s Data Team performs a function that is at the core of our business: we are responsible for building and maintaining the technical infrastructure to ingest the data sources, and deploy the models that drive our decision-making and software. Part of this role will be working directly with the Data Science team in order to make their models production-ready.
This is a full-time role reporting to our Head of Engineering and will be based out of our New York City office.
What You’ll Do Here
Integrating with third-party data sources (MLS and county tax data are primary sources, among others) to support our home transaction platform and Data Science initiatives
Building and maintaining ETL pipelines to support business intelligence
Building and maintaining model training and validation pipelines for our automated valuation model (AVM)
Deploying machine learning models (our AVM) to production so that analysts can use them to value the homes we make offers on
We’d Love to Hear From You if You Have:
3+ years of experience in a data engineer, software engineering or data science role
Experience using SQL and Python
Familiarity with Postgres, Redshift, and Airflow
Experience with machine learning frameworks like Tensorflow, LightGBM or XGBoost
Experience driving fast-paced projects from scratch to completion (e.g. building a new code base to tackle a complex problem) in a highly organized manner
A results-orientation with a high motor and an incredible attention to detail; able to drive projects from planning to completion with limited oversight
Demonstrated communication and interpersonal skills to work across diverse stakeholders and cross-functional teams
A low ego and can-do attitude; willingness to admit mistakes and work to remedy them
Comfort operating in an ambiguous environment where there’s not a set playbook on how to solve each problem
We’re proud to be recognized by Glassdoor, Inc. Magazine, Fast Company and Forbes on their lists of best places to work. We also have a 4.9 Glassdoor rating! Orchard is building the first one-stop-shop in real estate and we’re bringing together the most innovative professionals across real estate, business, marketing, technology and design. We also have some pretty great perks:
Up to 18 weeks of paid family leave
Employee discount on Orchard’s services
We’re currently working from home until it’s safe for employees to return to the office. We anticipate returning later this year and are excited to welcome people back to our offices and see one another in person. Until then, your interviews will all happen virtually. If there is anything we can do to make your process easier, don’t hesitate to let us know!
Orchard is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected status in accordance with applicable law.
To apply for this job please visit grnh.se.