About the team
The Senior Specialist, Data Science applies advanced analytical methods and machine learning techniques to solve complex business problems, generate actionable insights, and improve Zillow’s products and customer experiences. The role independently drives end‑to‑end data science projects, partnering with cross‑functional teams to define problems, build and evaluate models, and translate findings into scalable, data‑informed decisions.
About the role
- Lead end‑to‑end data science projects from problem framing and hypothesis design through model development, validation, and deployment, ensuring solutions are aligned with strategic business goals and customer needs.
- Develop advanced statistical and machine learning models (for example, prediction, recommendation, or optimization) using large, complex datasets, and rigorously evaluate performance to improve accuracy, fairness, and robustness.
- Design and implement efficient data pipelines, feature engineering approaches,



and experimentation frameworks in partnership with data engineering and product teams to enable scalable, repeatable analyses and model delivery.
- Translate complex quantitative findings into clear, compelling insights and recommendations for technical and non‑technical stakeholders, informing product roadmaps, operational decisions, and measurable business outcomes.
- Collaborate closely with product, engineering, analytics, and business partners to identify high‑impact opportunities, define success metrics, and prioritize data science work based on customer value and feasibility.
- Establish and advocate for best practices in data quality, model monitoring, documentation, and responsible AI usage, helping to continuously improve the reliability and trustworthiness of data‑driven solutions.
- Mentor less experienced team members by sharing domain knowledge, reviewing work, and contributing to a culture of learning, experimentation, and continuous improvement in data science methods

📌 Sr. Data Scientist (Ciudad de México)
🏢 Zillow
📍 Ciudad de México