Uber Machine Learning Interview Questions

This page represents some of the following in relation with Uber Data Science / Machine Learning interview questions:

  • Interview questions
  • Data Science challenge
  • Machine learning problems

These questions / problems etc have been gathered from different websites and blogs including Glassdoor, Github, Blogs etc.


Data Science / Machine Learning Interview Questions

  • Uber’s surge pricing algorithm including optimization techniques which can be used. Here is a great write up on The secrets of Uber’s mysterious surge pricing algorithm, revealed
  • How would you find / investigate an anomaly in a distribution?
  • What are different Time Series forecasting techniques?
  • Explain Principle Component Analysis (PCA) with equations?
  • How would you go about solving Multicollinearity?
  • What algorithms would you use to solve Uber driver accepting a ride request? How would you evaluate the results?
  • Questions related with probability and statistics fundamentals
  • Customer / Rider retention problem (Here is a great page on Customer / Rider retention

Data Science Challenge Questions

Here are some good links for helping you prepare for Uber Data Science / Machine Learning challenge questions:

Machine Learning Problems

You may also want to spend some time thinking through some of the following problems. The details in relation with some of the following can be found on this page, Uber Data Scientist

  • Marketplace optimization
  • Real-time marketplace forecasting
  • Product analytics
  • Surge pricing problem
  • Customer retention problem
  • Uber driving a rider request


Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Recent Posts

Coefficient of Variation in Regression Modelling: Example

When building a regression model or performing regression analysis to predict a target variable, understanding…

1 week ago

Chunking Strategies for RAG with Examples

If you've built a "Naive" RAG pipeline, you've probably hit a wall. You've indexed your…

2 weeks ago

RAG Pipeline: 6 Steps for Creating Naive RAG App

If you're starting with large language models, you must have heard of RAG (Retrieval-Augmented Generation).…

2 weeks ago

Python: List Comprehension Explained with Examples

If you've spent any time with Python, you've likely heard the term "Pythonic." It refers…

3 weeks ago

Large Language Models (LLMs): Four Critical Modeling Stages

Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and…

4 months ago

Agentic Workflow Design Patterns Explained with Examples

As Large Language Models (LLMs) evolve into autonomous agents, understanding agentic workflow design patterns has…

4 months ago