Interview Questions

Lucas G. - "Type I error (typically denoted by alpha) is the probability of mistakenly rejecting a true null hypothesis (i.e., We conclude that something significant is happening when there's nothing going on). Type II (typically denoted by beta) error is the probability of failing to reject a false null hypothesis (i.e., we conclude that there's nothing going on when there is something significant happening). The difference is that type I error is a false positive and type II error is a false negative. T"See full answer

Emiliano I. - "Look for the main variables and see if there differences in the distributions of the buckets. Run a linear regression where the dependent variable is a binary variable for each bucket excluding one and the dependent variable is the main kpi you want to measure, if one of those coefficients is significant, you made a mistake. "See full answer

Mark S. - "E(VAR(X))= VAR(X) VAR(X)= E[(X-E(X))^2] = E[X^2]-E[X]^2"See full answer

Mark S. - "Range captures the difference between the highest and lowest value in a data set, while standard deviation measures the variation of elements from the mean. Range is extremely sensitive to outliers, it tells us almost nothing about the distribution of the data, and does not extrapolate to new data (a new value outside the range would invalidate the calculation). Standard deviation, on the other hand, offers us an insight into how closely data is distributed towards the mean, and gives us some pr"See full answer

Hustle - "What does Netflix do? Netflix is a global entertainment company that produces and streams movies, TV shows, and documentaries. In recent years, it has also expanded into games and short-form content to increase engagement and strengthen its ecosystem. Why introduce podcasts? Netflix’s mission is to entertain the world. Podcasts offer a new, low-effort way for users to engage with Netflix’s stories and creators, especially during non-screen moments like commuting, exercising, or cooking. In"See full answer

Dhruv M. - "Thankyou for asking me this answer. What makes me unique in data analytics is my ability to blend technical skills with a strong business mindset. I don’t just focus on building dashboards or running analyses-I always tie the insights back to real business impact. During my internship at Quantara Analytics, for example, I didn’t just track supplier KPI's. I redesigned the reporting process, which cut manual work by 60% and improved decision-making. I’m also proactive about learning tools like Po"See full answer

Ilakiya R. - " Design & Architecture Overview: The system was a scalable, cloud-based web application built to manage customer data and automate service requests. Frontend: React.js: Chosen for its component-based architecture, reusable UI, and fast rendering using Virtual DOM. Backend: Node.js with Express.js: Selected for non-blocking I/O, scalability, and rapid API development. Database: MongoDB: Used for its flexible schema, scalability, and ease of handling unstructured data. Authentication: JWT"See full answer

Simran S. - "I recently led the development and implementation of a data analytics platform tailored for credit unions and mortgage companies, which was suffering from fragmented systems, inconsistent data fields across LOS platforms, and outdated reporting practices. Here's how I managed the full lifecycle: ✅ Initiation / Discovery Conducted executive interviews across five financial institutions to understand reporting and visibility gaps. Shadowed loan officers and underwriters"See full answer