Manager - Measurement Analytics & Decision Science, GCS
About the role
This role works on the technical core of JioHotstar's measurement stack - attribution modeling, incrementality testing, and the data infrastructure that proves advertiser outcomes. You'll work closely with the GTM/partnerships team who takes your models and findings to market; you own the rigor, the build, and the numbers that hold up under leadership and advertiser scrutiny.
Key Responsibilities
Deep-dive analysis & problem-solving: Investigate measurement gaps and discrepancies, dig into raw data, and independently drive issues to resolution before they're flagged by others
Model building: Build and maintain attribution, incrementality, and optimization models (e.g., ML-based CPI/install optimization) using statistical and ML techniques such as linear and logistic regression
Experimentation infrastructure: Design and run holdout/test-control experiments, ensuring correct randomization and experimental integrity
Engineering collaboration: Work with Engineering and Data Platform teams to productionize models, manage data pipelines, and enable privacy-safe data collaboration
Data quality & governance: Establish and maintain data quality standards across measurement pipelines - flag and resolve inconsistencies before they reach leadership or advertiser-facing outputs, and ensure attribution/incrementality data remains accurate and audit-ready
Reporting infrastructure & automation: Build and maintain reporting pipelines integrating internal systems, APIs, databases, and Google Sheets into BI platforms (e.g., Looker Studio); establish a single source of truth for business metrics
Cross-functional & leadership engagement: Partner with Product and GTM/Strategy to translate technical findings into leadership - and advertiser-ready proof points; present directly to senior leadership and defend methodology under scrutiny
Required Skills & Experience
4-6 years in data science, analytics, or measurement/attribution roles, ideally within ad-tech, martech, or a platform/marketplace environment
Strong coding proficiency in SQL and Python for data manipulation, analysis, and modeling
Solid grounding in statistical and ML techniques (linear regression, logistic regression, and related methods), with the judgment to choose the right method for the problem
Experience building visualizations and automated executive dashboards in tools like Databricks, Looker, or Data Studio
A demonstrated solution mindset with strong analytical rigor, comfortable being questioned on methodology and numbers
Ability to present complex technical findings clearly and confidently to leadership and non-technical stakeholders
Bachelor's or Master's degree in a quantitative field such as Statistics, Economics, Engineering, Computer Science, Mathematics, or a related discipline