Orchard is transforming the way people buy and sell their homes. Simplifying it, to the way it should have always been; fair and true to market, straightforward, easy. Every year in the U.S., $1.5 trillion of single-family residences transact, generating over $120 billion of fees in a process that has changed little in decades. For the average American, the home purchase and sale process takes months, creates anxiety, and is filled with uncertainty and hassle.
Orchard offers a modern alternative, making one of life's biggest decisions – the sale and purchase of a home – stress free, fair and simple.
Orchard launched in 2017 and was previously known as Perch. The company is headquartered in New York City, has 150+ employees and has grown 10x year over year. We have raised over $300 million in financing from top tier investors including: Firstmark, Accomplice, Navitas and Juxtapose.
Role and Responsibilities:
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.
There are four main areas that the Data Engineer will be enabling:
- 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 believe that there is a significant opportunity to make better decisions in single-family real estate through the use of data, and if we are successful in our work, Orchard will be able to transform the real estate industry.
- 2+ years of experience in a data engineer, software engineering or data science role. Experience working at a high-growth technology company is a plus.
- BA/BS degree in a quantitative discipline (Computer Science, Math, Statistics, Physics or Engineering) is desired but not required.
- Proficiency in SQL and Python is required. Familiarity with Postgres or Airflow is a plus.
- Experience with machine learning frameworks like Tensorflow, LightGBM or XGBoost is a strong plus.
- 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
- Results oriented with a high motor and an incredible attention to detail; able to drive projects from planning to completion with limited oversight
- Entrepreneurial - comfortable talking to stakeholders to understand business needs, running small tests to validate assumptions, and refining requirements based on results
- Excellent analytical and critical thinking skills
- A low ego and can-do attitude; willingness to admit mistakes and roll up your sleeves to remedy them
- Flexibility to prioritize deliverables and re-prioritize them at a moment’s notice
- Comfort operating in an ambiguous environment where there's not a set playbook on how to solve each problem
- Excellent written and spoken communication skills