Senior Data Scientist

TL;DR

Senior Data Scientist (Machine Learning/Data Science): Leading end-to-end data science projects that build statistical and machine learning solutions for real estate products and customer experiences with an accent on experimentation, scalable data pipelines, and model reliability. Focus on designing predictive, recommendation, and optimization models, evaluating causal impact, and translating complex findings into product and business decisions.

Location: Remote within the United States; employees may live in any of the 50 states, with limited exceptions.

Salary: $141,200–$225,600 or $148,600–$237,400 annually, depending on location.

Company

A large U.S. real estate technology platform that helps customers buy, sell, finance, and rent homes.

What you will do

• Lead data science projects from problem framing and hypothesis design through model development, validation, and deployment.
• Develop and evaluate predictive, recommendation, and optimization models using large, complex datasets.
• Build feature engineering approaches, data pipelines, and experimentation frameworks for scalable analysis and model delivery.
• Translate quantitative findings into recommendations for product roadmaps, operational decisions, and business outcomes.
• Partner with product, engineering, analytics, and business teams to define opportunities, metrics, and priorities.
• Establish practices for data quality, model monitoring, documentation, responsible AI, and team mentoring.

Requirements

• Bachelor’s degree in statistics, mathematics, computer science, engineering, economics, or a related quantitative field, or equivalent experience.
• 8+ years of professional experience applying statistical analysis, machine learning, or advanced analytics to business problems.
• Experience working with large, complex datasets using Python or R and SQL.
• Experience designing and evaluating experiments or causal inference approaches.
• Experience collaborating with cross-functional teams to operationalize data science solutions at scale.
• Must be located in the United States.

Culture & Benefits

• Fully remote work without a permanent corporate office workplace.
• Equity awards may be provided based on experience, performance, and location.
• Collaborative environment spanning data science, product, engineering, analytics, and business teams.
• Focus on inclusive collaboration, learning, experimentation, and continuous improvement.