Inspiration

Companies face 11th hour issues when employees unexpectedly resigns. It takes a lot of effort to find an equivalent replacement

What it does

Takes past dataset of company, and insights to predict the employees likely to quit

How we built it

Used python to analyze huge dataset to extract meaningful insights, and determine factors which influence an employee to quit

Challenges we ran into

-Learning Python with no prior experience on-the-fly -Brainstorming the possible insights, and sorting out the useful ones

Accomplishments that we're proud of

-Learned new language -Better understanding of data science -Useful insights

What we learned

-Time is important -Be careful while selecting team members -Make best use of each team member

What's next for Employee turnover Estimator

Taking decisions based on insights, such as:

  • One-to-one talk with employees on regular periods -Appraisals -Internal skill training -Searching for replacement employee

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