Zillow
From Zillow's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
We are seeking an experienced professional to support our workforce expansion in India.
The Housing Trends Metrics and Forecasting team builds and maintains the data pipelines, metric definitions, and analytical methods behind Zillow’s housing market reporting, internal business metrics, forecasting, and market intelligence products. The team works across listing, transaction, and property-attribute data to produce recurring housing metrics that provide timely insight into real estate market trends and inform business forecasting, financial analysis, economic research, and sales and marketing operations.
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 Zillow’s mission. We bring deep experience working across diverse teams in a dynamic, high-growth environment, balancing strategic thinking with hands-on execution to drive meaningful business impact. We are seeking an experienced professional to support our workforce expansion in India.
Zillow is looking for an Applied Scientist to join Housing Trends Metrics and Forecasting.
In this role, you will own scoped, high-impact work that improves the reliability, quality, and maintainability of Zillow’s published housing metrics. You will support recurring metric publication, investigate metric anomalies and possible data outages, strengthen data quality checks, and partner closely with engineers on pipeline migrations and system improvements.
This role is well suited for someone who is comfortable moving between analytical investigation and production data work. You should be able to use SQL, Python, and Spark to debug issues, validate upstream changes, improve metric logic, and build durable solutions for live metric systems.
You should also be able to take ambiguous measurement or data quality problems, break them into manageable pieces, and clearly explain both the technical trade-offs and business impact of your recommendations.
Support recurring publication of housing metrics by monitoring outputs, validating changes, and resolving issues before they affect downstream consumers.
Investigate metric anomalies, suspected bugs, and possible data outages by tracing issues across source data, transformation logic, and publication workflows.
Design and implement stronger data quality checks, validation workflows, and monitoring patterns for production metric pipelines.
Partner with engineers to migrate pipelines, reduce fragile upstream dependencies, and improve system reliability and maintainability.
Evaluate the impact of upstream schema, logic, or source-data changes against historical baselines and communicate revisions, caveats, and trade-offs to stakeholders.
Improve metric definitions, documentation, and operational workflows so recurring processes are more reproducible, explainable, and resilient.
This role has been categorized as an Office position. “Office” employees regularly work at the Zillow India office for approximately 80 to 100 percent of their time each month. Employees must live within a reasonable commuting distance of the office. Zillow has not defined a reasonable distance, and expects employees will use judgment in determining this for themselves and understand the implications re: time commitment and cost of daily commute.
In addition to a competitive base pay, employees in this role are eligible for incentive compensation subject to applicable laws and relevant Zillow policies. Actual amounts will vary depending on experience, performance and location.
You can independently own a well-scoped problem and drive it from investigation through validated recommendation or implementation.
You know how to translate a business or measurement question into a data plan, implement the analysis, test the output, and clearly explain the result.
You are comfortable working with large operational datasets and with the engineering realities of production metrics, including schema changes, backfills, data latency, historical reproducibility, and release validation.
You care about methodological rigor, but you also know how to deliver practical improvements to a live system.
You communicate clearly with both technical and non-technical stakeholders and work effectively in close partnership with engineers.
Master’s degree with 3+ years of experience, or PhD with 1+ years of experience, in statistics, economics, data science, computer science, mathematics, engineering, operations research, or a related quantitative field.
Strong SQL skills, including complex joins, window functions, aggregations, and debugging metric logic over large relational datasets.
Strong Python skills for analytical development, validation tooling, and reproducible workflows; experience with PySpark or Spark for distributed data processing.
Experience working in Databricks or a similar large-scale data platform, including warehouse-style tables, scheduled jobs, and production data workflows.
Experience investigating data quality issues, metric anomalies, or production data bugs and turning findings into durable fixes.
Experience writing maintainable code in a shared codebase using version control, code review, and testing or validation frameworks.
Good communication skills, with the ability to explain technical trade-offs, data caveats, and metric impacts to both technical and non-technical partners.
Experience building or improving automated data quality checks, validation frameworks, or monitoring for production data pipelines.
Experience managing noisy operational data and complex upstream dependencies.
Experience validating backfills, historical revisions, or upstream logic changes against established baselines.
Experience designing and improving analytical datasets or metrics end to end, from source understanding through transformation, validation, and stakeholder communication.
Past experience partnering closely with data or software engineers on pipeline migrations or system improvements.
Interest in housing market data, operational metrics, or applied measurement problems in production systems.
Get to know us
At Zillow, we’re reimagining how people move—through the real estate market and through their careers.
As the most-visited real estate platform in the U.S., Zillow helps millions of customers navigate buying, selling, financing, and renting with greater ease and confidence. Our teams in India play a critical role in building and scaling the technology, products, and operations that power this experience.
Whether you’re working in tech, operations, or shared services, you’ll collaborate with global partners to solve meaningful problems and help more people make home a reality.
Zillow is honored to be recognized among the best workplaces in the U.S.. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, maternity status, HIV status, or veteran status. Reasonable accommodations will be provided to candidates with disabilities, in accordance with applicable policies.
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