Applied Scientist

🕒 October 7

🏄 California, Colorado, +15 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🌺 Hawaii – Remote 🌽 Illinois – Remote 🦞 Maine – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote ❄️ Minnesota – Remote ⚓ Rhode Island – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $132.4k - $222.6k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🧬 Research Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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Zillow

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2006

🏠 Real Estate

🛍️ eCommerce

👥 B2C

💰 $4.1M Post-IPO Equity on 2012-12

Real Estate • eCommerce • B2C

Zillow is a leading real estate and property rental marketplace that provides comprehensive information on homes, apartments, and properties for sale or rent. It offers users tools to search for properties, calculate mortgage rates, and connect with real estate agents. The platform also features innovative algorithms that provide Zestimates, which are estimated market values of homes. Zillow is a go-to resource for individuals looking to buy, sell, or rent properties, as well as for agents and brokers who want to reach a wider audience.

📋 Description

• Develop hierarchical forecasts for the housing market at various regional levels • Identify economic and demographic drivers of housing market growth across regions • Extract features that predict housing market trends 1 to 2 years in the future • Collaborate with engineering to deploy models into production environments • Contribute to monthly forecast production • Communicate forecast performance and housing market outlook to business partners and senior leadership • Develop scenario models covering a wide range of housing market outcomes • Contribute to a company-wide stress-testing framework • Conduct independent research and apply research methods to real-world problems

🎯 Requirements

• Strong interest and understanding of the housing market and influencing economic factors • Experience with time series, panel data, and hierarchical forecasting • Strong foundation in traditional econometric methods and modern machine learning techniques • Proficiency in data cleaning, preprocessing, and feature engineering for time series data • Experience with large-scale datasets • Familiarity with distributed computing frameworks such as Spark • Ability to design and implement model evaluation and validation strategies, including cross-validation and backtesting • Experience with time series forecasting accuracy and performance metrics • Proficiency in cloud-based platforms and tools for deploying and monitoring machine learning models • Proficiency in building AI agents to automate manual work • Excellent verbal and written communication skills • 2+ years of proven experience working in time series/spatial forecasting • Master’s or PhD degree in Mathematics, Statistics, Economics, Econometrics, Physics, Earth Sciences, or a related scientific field

🏖️ Benefits

• Equity awards based on experience, performance, and location • Remote work from a physical location of choice • Flexible work from wherever employees are most productive • Equal employment opportunity and inclusive work environment • Disability or special-need accommodation

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