My data science journey began with a crisis.
At 9:01am on Monday morning, my phone buzzed with a PagerDuty alert. Instinctively, I pulled up the corporate dashboard and saw that loan approval rates had doubled overnight.
My heart began pounding.
I used to be a risk analyst on the time managing a lending portfolio. Approving loans for a higher-risk segment could have a big effect on loss rate.
Bleary-eyed, I dove into the info.
I frantically:
- Wrote SQL queries to tug data,
- Analyzed data in Python attempting to spot anomalies,
- Searched for patterns that might explain the sudden spike in approval rates.
I discovered that one specific feature within the credit model had drifted.
Seems it was an easy timezone error.
This incident marked a turning point in my profession, and was the start of my journey going from data analyst to data scientist.
