DS&I Interview Prep

Coding

Questions cover your approach to coding and data manipulation using SQL and Python/R, including writing clean, efficient queries and scripts, applying best practices, and solving practical data problems.

Applied Statistics & Machine Learning

Expect questions on machine learning case studies, applied statistics, and causal inference, including building and interpreting predictive models and applying statistical reasoning to real-world problems.

Product Analytics

This topic examines your understanding of product analytics, including the Snapchatter  journey on Snapchat, defining success metrics, and using data to evaluate product performance and inform decisions.

Experimentation & A/B Investigation

The interview covers standard A/B testing and experimentation, including test setup, metric tradeoffs, best practices, test validity, and network effects.

Collaboration

A meeting with a cross-functional partner, such as a PM, Designer, or Engineer, explores how you collaborate, tell stories with data, drive impact, and solve problems.

Measurement Frameworks & Solutions

Questions cover applying measurement methodologies to advertiser business questions, including selecting appropriate approaches and supporting or building custom solutions that improve campaign measurement, performance, and optimization.

Insights, Analysis, & Research

Discussion includes accessing, analyzing, interpreting, and communicating ad performance insights, with an emphasis on identifying meaningful trends, diagnosing performance drivers, and translating findings into clear recommendations for technical and non-technical audiences.

Thought Leadership & Collaboration

Focuses on developing new approaches that improve measurement practices, serving as a trusted measurement consultant to strategic advertisers, and collaborating with internal and external partners to solve complex problems and drive impact.

In the final presentation, you may demonstrate these skills by approaching a Marketing Science scenario, turning a complex dataset into a clear story, and proposing a thoughtful strategy.