JacobTews / hiring_pipeline_analysis

Sample project: Hiring pipeline analysis

I work for a company that helps source prospective workers for companies needing talent. Today I got a note from Pip Lane, our Director of Marketing.

Jacob-

I've sent you the link to the hiring data from August. I'm curious to know a few things:

1. In general, we want to minimize the $ spend per hire. What companies, role-types, and positions performed well? Which companies, role-types, and positions did not perform well?
2. How much capital was spent on positions without a single hire?
3. What sort of candidate funnel dynamics can be observed for positions that perform well vs ones that do not? For example, is there a difference in application expiration rate for positions that perform well vs the ones that do not? How quickly is the buildup of approved applications dispersed to downstream funnel states for positions that perform well vs ones that do not?

Looking forward to hearing your insights at the meeting next week. Thanks!

-Pip

🎯 Goals

• Explore the dataset
• Answer Pip's questions
• Create visuals/presentation that tells the story of the pipeline

🏗 Dependencies

• Python 3.9.7
• numpy
• pandas

📂 Data

💡 Insights and Impact

🛠 Want to dig into my code?

Here's the notebook, a bit messy but still worth perusing!