Business Problem: To ensure there is no discrimination between employees, it is imperative for the Human Resources department of Delta Ltd

Business May 25, 2022

Business Problem:

To ensure there is no discrimination between employees, it is imperative for the Human Resources department of Delta Ltd. to maintain a salary range for each employee with similar profiles

Apart from the existing salary, there is a considerable number of factors regarding an employee’s experience and other abilities to which they get evaluated in interviews. Given the data related to individuals who applied in Delta Ltd, models can be built that can automatically determine salary which should be offered if the prospective candidate is selected in the company. This model seeks to minimize human judgment with regard to salary to be offered.

Goal & Objective: The objective of this exercise is to build a model, using historical data that will determine an employee's salary to be offered, such that manual judgments on selection are minimized. It is intended to have a robust approach and eliminate any discrimination in salary among similar employee profiles
Description

Dear Participants,

Please submit your project notes -1 here.

Review Parameters	Review points
1) Introduction of the business problem	4
a) Defining problem statement
b) Need of the study/project
c) Understanding business/social opportunity

2)Data Report	2
a) Understanding how data was collected in terms of time, frequency and methodology
b) Visual inspection of data (rows, columns, descriptive details)
c) Understanding of attributes (variable info, renaming if required)

3) Exploratory data analysis	10
a) Univariate analysis (distribution and spread for every continuous attribute, distribution of data in categories for categorical ones)
b) Bivariate analysis (relationship between different variables , correlations)
a) Removal of unwanted variables (if applicable)
b) Missing Value treatment (if applicable)
d) Outlier treatment (if required)
e) Variable transformation (if applicable)
f) Addition of new variables (if required)

4) Business insights from EDA	4
a) Is the data unbalanced? If so, what can be done? Please explain in the context of the business
b) Any business insights using clustering (if applicable)
c) Any other business insights

Total	20

Expert Solution

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