Zillow

Applied Scientist

India · Work style not stated · Full time

Apply on the employer’s site ↗See how well you match this job

You apply directly with the employer. ROLIVA does not submit applications from this page and is not the employer.

About the role

Description from the employer’s posting. Check the employer’s page for the current version.

  • EmployerZillow
  • LocationIndia
  • Work styleWork style not stated
  • Employment typeFull time
  • Employer posted

About the team

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.

Show full description

About the role

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.

You Will Get To

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.

Who you are

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.

Basic Qualifications

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.

Preferred Qualifications

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 ofFORTUNE 100 Best Companies to Work For® in 2025, and included on thePEOPLE Companies That Care® 2025list, 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.

Staying safe while you apply

  • Never pay to apply, interview or accept an offer. ROLIVA never asks you for payment to apply to a job.
  • Apply only through the official “Apply on the employer’s site” button, on the employer’s own site, and check that a recruiter’s email uses that employer’s own domain rather than a free email address.
  • Be cautious of an offer made with no real interview, or pressure to decide quickly or share financial details early.

Does something look wrong with this listing? Use “Report broken link” in the role details, or read ROLIVA’s full job-safety guidance ↗.

Preparing for this role with ROLIVA

  • Check the fit.

    Compare the requirements with the experience you have confirmed, including gaps.

  • Prepare honestly.

    Build interview stories and application drafts from your own evidence.

  • Keep track.

    Save the role and record your own application status and follow-ups.

Create a free workspace or log in.

Data scientist jobs in Bengaluru

ROLIVA currently lists 61 open roles like this in Bengaluru.

Employers hiring for this

  • Fractal12 open roles
  • Hewlett Packard Enterprise6 open roles
  • HP4 open roles
  • Sigmoid3 open roles
  • Wabtec3 open roles

Top skills asked for

Listings whose description mentions each term. A mention is not a requirement.

At a glance

  • Employment typeFull time
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.

SQL Python Spark

Explore similar roles

Similar jobs

Oshkoshcorporation

Sr. Data Scientist

United States

Work style not statedFull time