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Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

Statistics

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

A/B Testing & Experimentation

Job Title: Data Engineer Experience: 5 to 7 YearsBudget: 17 to 25 LPALocation: BangaloreType: Full-Time <ul><li>Design and Development:</li><li>Design, develop, and maintain scalable and robust data pipelines (ETL/ELT) using PySpark on the Databricks platform.</li><li>Implement data ingestion strategies to load data from various sources (e.g., streaming, APIs, databases, files) into the Data Lake/Data Warehouse.</li><li>Write optimized and complex SQL queries for data extraction, transformation, and loading.</li><li>Platform & Optimization:</li><li>Leverage expertise in a Cloud Platform (AWS/Azure/GCP) for cloud-native data services, storage solutions (e.g., S3, ADLS, GCS), and compute resources.</li><li>Optimize and fine-tune Spark jobs and Databricks clusters for performance, cost efficiency, and reliability.</li><li>Ensure data quality, integrity, and security across all data lifecycle stages.</li><li>Collaboration & Operations:</li><li>Collaborate with Data Scientists, Analysts, and other engineering teams to understand data requirements and deliver solutions that meet business needs.</li><li>Implement and maintain CI/CD pipelines and version control (e.g., Git) for data pipeline deployments.</li><li>Monitor and troubleshoot production data pipelines and proactively address issues.</li></ul>

Job Title: Data EngineerExperience: 6 to 10 YearsBudget: 20 to 30 LPALocation: BangaloreType: Full-Time We are hiring sharp, hands-on Data Engineers to build scalable data solutions and drive performance across both traditional and cloud-based data platforms. Key Roles and Responsibilities.<ul><li>5+ years of hands-on experience in Data Engineering</li><li>Strong command over SQL, Python, and PySpark for data manipulation and analysis</li><li>Deep experience with data warehousing concepts and implementation in cloud environments (Azure/AWS)</li><li>Proficiency in data modeling techniques for cloud-based systems</li><li>(Databricks, Snowflake)</li><li>Solid understanding of ETL/ELT processes and best practices in cloud architectures</li><li>Experience with dimensional modeling, star schemas, and data mart design</li><li>Strong analytical thinking and problem-solving skills</li></ul>

Question	Topic	Difficulty	Ask Chance
Boarding Times Bias	Statistics	Medium	Very High
Hundreds of Hypotheses	Statistics	Medium	Very High
Random Bucketing	A/B Testing & Experimentation	Medium	Very High

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