Senior Data Scientist (Marketing Analytics & Data)

Zillow · Bengaluru

  • Experience7–11 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Zillow

Zillow is hiring in Bengaluru in real estate construction. This role looks for around 7+ years of experience.

Skills

  • Marketing Mix Modeling
  • Marketing Attribution
  • Incrementality Testing
  • Causal Inference
  • Geo-Testing
  • Difference-in-Differences
  • Synthetic Controls
  • Uplift Modeling
  • Performance Forecasting
  • Budget Optimization
  • SQL
  • Python
  • R

The role

A data scientist at a real-estate technology company applies marketing mix modeling, causal inference, and marketing attribution to measure campaigns, forecast performance, and optimize budgets. The role also uses SQL and Python to operate production analytics and guide marketing leaders.

Full job description

Requirements:

8+ years of hands-on experience in data science, marketing analytics, or applied measurement. Deep expertise in Marketing Mix Modeling (MMM): methodology, tooling, business integration, and stakeholder communication.

Strong knowledge of marketing attribution, incrementality testing, and causal inference methods (geo-testing, diff-in-diff, synthetic controls, uplift modeling).

Experience with performance forecasting and budget optimization in a marketing context.

Proven ability to manage and influence senior stakeholders across functions and geographies.

Strong executive communication skills: comfortable presenting complex methodology and business implications to senior marketing and business leaders.

Deep proficiency in SQL and Python or R; experience operating in production analytics environments.

Comfort operating in a globally distributed team environment with US-based counterparts.

Nice to Have

Exposure to offline marketing analytics, brand measurement, or upper-funnel attribution.

Experience scaling and modernizing legacy marketing measurement infrastructure.

Familiarity with dbt, Databricks, Snowflake, Airflow, or comparable data infrastructure.

Experience building or managing analytics teams across multiple geographies.