Data Scientist, Partner Analytics (Remote)

Zillow Group Inc.; United States; Hybride; USD 126 000 - 201 000; Plein temps

Avantages offerts par ce poste

Equity awards

Remote work

Résumé du poste

Zillow Group’s Partner Analytics team is hiring a Data Scientist to lead analytics across our product portfolio and drive insights for better decisions and customer experiences. You will design, develop, and deploy end-to-end analytical and ML solutions, collaborating with product, engineering, and business teams to frame questions and define success metrics.

You will build scalable data pipelines, features, and models using modern ML tooling, ensure production reliability, and apply rigorous

Qualifications

• Lead analytics to uncover insights that drive business decisions and customer experiences across our product portfolio.
• Frame ambiguous questions into testable hypotheses, define success metrics, and translate requirements into analytics or modeling approaches.
• Build, validate, and maintain scalable data pipelines, features, and models using modern data and ML tooling.

Responsabilités

• Partner with product, engineering, and business stakeholders to frame problems and drive data-informed decisions.
• Translate requirements into robust analytical or modeling approaches and communicate results clearly to diverse audiences.
• Apply sound experimentation practices (A/B testing, backtesting, error analysis) to measure impact and guide iteration.

Connaissances

Data science

Machine learning

SQL

Python

Experimentation

Communication

Description du poste

Zillow Group’s Partner Analytics team is hiring a Data Scientist to lead analytics across our product portfolio and drive insights for better decisions and customer experiences. You will design, develop, and deploy end-to-end analytical and ML solutions, collaborating with product, engineering, and business teams to frame questions and define success metrics.

You will build scalable data pipelines, features, and models using modern ML tooling, ensure production reliability, and apply rigorous