Splunk Data Science Interview Questions

90 of Fortune 100 use Splunk.

Splunk turns machine data into answers. It can give you the answers you need to solve your toughest IT, security and business challenges — with the option to deploy on-premises, in the cloud or via a hybrid approach. In todays world where Machine Data is generated every second, a tool like Splunk is very important. There are close to 1900+ Splunk Apps which help you ingest data from machines and get insights from them. Splunk is not only good place for Data Scientists because their product reads so much data but also a tool which Data Scientists use. This interesting dynamic makes it worthwhile to build a Data Science career at Splunk.

Source: Splunk
Interview Process

Their interview process consists of a coding challenge in a coderpad test. Once you clear the test, there is an Onsite interview. In the onsite interview there are three interviews focused on Data Engineering, Analysis and ML. That is followed by a meeting/lunch with manager at the end as the fourth interview. Splunk is in the business of building ETL pipelines and questions related to those aspects are very important.

Important Reading
Source: ML for maintenance ops
AI/Data Science Related Questions
  • Write a function to Reverse string elements in an array.
  • Implement an AVL tree.
  • How do you optimize model parameters during model building?
  • Find max of an array.
  • How does the K-Means algorithm works?
  • Design an org-chart server. Server (preferably multi-threaded) reads the sample file containing employee data.
  • What attracted you to Splunk, and made you want to apply for this position?
  • What is the difference between a join and a relate?
  • What is a ETL pipeline?
  • What is the difference between bar plot and histogram?
Reflecting on the Questions

The data science is embedded in the Splunk product. There is huge amount data that goes through the app which explains some of the questions that they ask frequently. Data Visualization and Analytics is at the core of this interview. Good ETL knowledge and a knack for great data story telling can surely land you a job at the world’s largest machine data consumer.

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The sole motivation of this blog article is to learn about Splunk and its technologies helping people to get into it. All data is sourced from online public sources. I aim to make this a living document, so any updates and suggested changes can always be included. Please provide relevant feedback.