Machine Learning Engineer in New York, NY

$80K - $100K(Ladders Estimates)

Perch   •  

New York, NY 10001

Industry: Real Estate & Construction

  •  

Less than 5 years

Posted 53 days ago

The Company

Perch is transforming the way people buy and sell their homes. Simplifying it all, 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. Perch offers a modern alternative, making one of life's biggest decisions -- the sale and purchase of a home –so stress free, fair and simple that people cannot imagine any other way.


Perch is headquartered in New York City and has 85 employees in New York and Texas. We have raised $250 million in financing from top tier investors including: Firstmark, Accomplice and Juxtapose.



Role and Responsibilities

Perch's Data Team performs a function that is at the core of our business: we are responsible for obtaining, integrating with, vetting, and building the technical infrastructure to ingest the critical data sources 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-worthy.


There are four main areas that the Machine Learning Engineer will be enabling: Integrating with third-party data sources (MLS and county tax data are primary sources, among others) to support our application (Atlas) and Data Science initiativesBuilding and maintaining ETL pipelines to support business intelligenceBuilding 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 that if and only if we are successful in our work will Perch be able to transform the real estate industry. We are currently seeking a talented Machine Learning Engineer for our team. The ideal candidate possesses good technical judgment, which we define as the ability to design and build data pipelines that can be deployed quickly, require minimal maintenance, and allow for rapid iteration by data scientists, application engineers, and other data stakeholders.


The candidate should be accustomed to delivering results in hours and days rather than weeks or months. The successful candidate will be team-oriented and feel comfortable with the dynamic pace of a startup, participating in all phases of product development from proof of concept to implementation and maintenance. The ability to clearly communicate in both a concise and precise manner is an absolute must. This position reports to the Head of Technology.


  • Researching and evaluating mathematical models
  • Implementing and testing of models in Python
  • Performing data analysis on large data sets
  • Communicating results of work with teammates and company stakeholders


Professional Qualifications

  • 3-4 years of relevant professional experience
  • Degree in relevant courses of study (e.g., Statistics, Mathematics, Computer Science, Physics) desired but not required
  • Excellent written and spoken communication skills
  • Entrepreneurial - comfortable talking to stakeholders to understand business needs, running small tests to validate assumptions, and refining requirements based on results
  • Self-motivated and gets stuff done
  • Proficiency in Python - required
  • Deep knowledge of SQL - required


Personal Qualifications

  • 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
  • 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


Valid Through: 2019-10-21