Analytics Interview Puzzles

In an analytics interview, multiple skills are assessed by the organizations. Some of the skills required and assessed by the interviewers are

Logical Thinking

Technical Tool Skills: SAS/R/Python

Statistical/Machine Learning Techniques

Functional or Industry Expertise

Analytical Frameworks and Applications

One of the ways to assess candidates on Logical Thinking is by giving analytical puzzles or case studies. Some of the puzzles asked in the interviews are listed below.
Puzzle 1:Cake Cutting Puzzle - There is a birthday cake and it needs to be cut into 8 equal pieces in exactly 3 cuts. How will you do it?

Solution:
Step 1 – First cut the cake horizontally down the center and then vertically through the center. This will give 4 equal pieces.
Step 2 – Stack the 4 pieces one above the other to make a pile, then in the 3rd cut just cut through them into half. The result will be 8 equal pieces of cake.

Read more puzzles and solutions.

Decision Tree Explained

A decision tree is a hierarchical or tree like representation of decisions. Decision Tree is a technique to iteratively break input data (or node) into two or more data samples (or nodes).  And this recursive partitioning of input data (or node) continue until it meets specified condition(s).

Decision Tree is a method for objective segmentation.  Segmentation – A Perspective

The aim of decision tree based recursive partitioning data is to improve impurity measure of the output node(s). These nodes are called child node and the input node as parent node.  If an algorithm break into two node at each stage, is called binary decision tree.

Example, banks and financial institutions grant credit facility after evaluating credit risk involved. Credit risk involved in credit decisions is evaluated using Credit Scorecard [Credit Score: What is it and how is it developed?]. Also, there are a few additional decisions involved in credit underwriting [Credit Underwriting: Minimize credit risk losses using Data Science and Analytics].

Read more @  Decision Tree: Statistical Tool

String Manipulations using R

Text Mining and Text Analytics are getting increased attention, thanks to open source technologies and digitization. Huge volume of textual data is generated and organizations are looking for ways to learn and create competitive advantage.

String manipulation is one of the key steps in processing text data for insights. We have covered some of the R functions to help for

• Removing white spaces- trailing, leading or in-between from a string
• Extracting fisrt, last or nth word from a string
• Getting substring from an input string

Want more details and examples