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Zillow Group

real estate marketplace · mortgage lending

Applied Scientist, Forecasting Bengaluru (India)

BangalorePosted 1 month ago
Data Science And StatisticsMid-levelFull Time; Regular
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About the team An Applied Scientist has a masters or PhD and is able to work with complex big data across multiple databases and sources, stitching together a cleaner version of data that is the foundation for analysis. Often times, Applied Scientists have to understand and research the intricacies of the data itself before using it to answer broader questions. More advanced coding and machine learning tools are usually required. Applied Scientists and Economists sometimes have to work together on a project, as their skill sets are complimentary. On occasion, Applied Scientists will also write research briefs, but more often than not they focus on methodology. Zillow Group is a strategic, mission-driven organization focused on delivering exceptional experiences and measurable outcomes. Our work spans cross-functional partnership, scalable programs and operational excellence in support of Zillows mission. We bring deep experience working across diverse teams in a energetic, high-growth setting, balancing strategic thinking with hands-on execution to drive meaningful business impact. We are seeking an experienced qualified to support our workforce expansion in India. About the role Design and evaluate statistical, econometric, and machine learning methods for forecasting problems. Your work will play a central role in increasing forecast accuracy and accelerating delivery timelines Build backtesting and validation frameworks to assess forecast accuracy, stability, and downstream forecast impact. Own the endtoend modeling lifecycle, including scoping, feature engineering, model development, experimentation, deployment, monitoring, and model explainability. Translate forecasts into clear insights and recommendations for senior leadership, helping stakeholders understand drivers, uncertainty, and tradeoffs that guide Zillows strategy. Quantify uncertainty and clearly communicate model confidence, limitations, and trade-offs to technical and non-techn .

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