Crack SQL for Data Science Interviews

Hosted by Anirban Bhattacharyya

Fri, May 15, 2026

5:00 PM UTC (30 minutes)

Virtual (Zoom)

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SQL for data science interviews
Anirban Bhattacharyya
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What you'll learn

Solve interview-style SQL problems confidently by breaking down ambiguous questions into clear query logic.

Apply advanced SQL patterns including joins, CTEs, window functions, aggregations, funnels, cohorts, retention analysis

Communicate analytical reasoning clearly by explaining assumptions, edge cases, metrics, and tradeoffs

Why this topic matters

SQL is a core skill for data science interviews and real analytics work. Students should care because it shows how they think with data, not just syntax. This lesson helps them solve ambiguous problems, define metrics, handle edge cases, and explain logic clearly—building confidence for interviews and stronger on-the-job analysis.

You'll learn from

Anirban Bhattacharyya

Seasoned data scientist with more than 10 years of experience in data science

Anirban is a Senior Data Scientist at Atlassian with more than 10 years of experience applying analytics, experimentation, and causal inference to real-world business problems. Over the course of his career, he has worked at companies including Google, Dropbox, Pinterest, eBay, and American Express, where he partnered with product, growth, and marketing teams to drive better decisions through data.


His work has focused on high-impact questions such as measuring the effect of product changes, understanding customer behavior, optimizing growth initiatives, and evaluating interventions when clean randomized experiments are not possible. Across these roles, he has developed deep expertise in causal inference, statistical modeling, experimentation, and product analytics, with a strong emphasis on making rigorous methods useful in messy, high-stakes business settings.


Anirban brings a practical, industry-centered perspective to teaching. Rather than focusing only on theory, he is passionate about helping students learn how to choose the right causal method, validate assumptions, diagnose failure modes, and communicate findings in a way that earns stakeholder trust and drives action.

Previously at

Atlassian
Pinterest
Dropbox
eBay
Google
See all products from anirbanbhattacharyya

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