Problem Statement
Scaler is an online tech-versity offering intensive computer science & Data Science courses through live classes delivered by tech leaders and subject matter experts. The meticulously structured program enhances the skills of software professionals by offering a modern curriculum with exposure to the latest technologies. It is a product by InterviewBit.
You are working as a data scientist with the analytics vertical of Scaler, focused on profiling the best companies and job positions to work for from the Scaler database. You are provided with the information for a segment of learners and tasked to cluster them on the basis of their job profile, company, and other features. Ideally, these clusters should have similar characteristics.
Dataset:
Dataset Link: scaler_kmeans.csv
Data Dictionary:
‘Unnamed 0’ - Index of the dataset
Email_hash - Anonymised Personal Identifiable Information (PII)
Company_hash - This represents an anonymized identifier for the company, which is the current employer of the learner.
orgyear - Employment start date
CTC - Current CTC
Job_position - Job profile in the company
CTC_updated_year - Year in which CTC got updated (Yearly increments, Promotions)
Concept Used:
Manual Clustering
Unsupervised Clustering - K- means, Hierarchical Clustering