Data Scientist, Trust & Safety - Rentals

Zillow Zillow · Consumer · United States · Remote

Data Scientist role focused on building and deploying end-to-end machine learning solutions for trust and safety in the rentals domain. This involves data preparation, feature engineering, model development, validation, and operationalization, with a focus on creating scalable data products and insights for business decisions. The role emphasizes collaboration with cross-functional teams and applying experimentation practices.

What you'd actually do

  1. With guidance from your manager, lead the design, development, and deployment of end-to-end analytical and machine learning solutions that address moderately complex business problems and customer use cases.
  2. Partner with product, engineering, and business stakeholders to frame ambiguous questions into testable hypotheses, define success metrics, and translate requirements into robust analytical or modeling approaches.
  3. Build, validate, and maintain scalable data pipelines, features, and models using modern data and ML tooling, ensuring reliability, reproducibility, and performance in production environments.
  4. Analyze large, complex datasets to uncover trends, drivers, and opportunities, and clearly communicate findings and recommendations to technical and non-technical audiences.
  5. Apply sound experimentation and evaluation practices (e.g., A/B testing, backtesting, error analysis) to measure impact, compare alternatives, and guide iteration on models and data products.

Skills

Required

  • Bachelor’s degree in a quantitative field
  • 5+ years of experience applying data science, advanced analytics, or machine learning
  • Experience designing and implementing end-to-end analytical or ML solutions
  • Experience working with large datasets and modern data ecosystems
  • Experience collaborating with cross-functional partners

What the JD emphasized

  • end-to-end analytical and machine learning solutions
  • production-quality models
  • scalable data products
  • advanced analytical methods
  • machine learning techniques
  • production environments

Other signals

  • production-quality models
  • scalable data products
  • advanced analytical methods
  • machine learning techniques