Project detail
Job Satisfaction with PyMC
Bayesian model for estimating job satisfaction and detecting at-risk employees with visual support.
Highlights
- Job satisfaction prediction
- Thresholds for risk cases
- Flutter frontend for loading and review
- Focused on retention and wellbeing
No public repository or demo link is published for this project yet.
Architecture
FastAPI service backed by PyMC and Flutter visualization for loading records and viewing estimated risk
Challenges
- Defining a useful intervention threshold
- Maintaining score interpretability
- Avoiding noise in input data
Outcome
A tool for detecting satisfaction issues before they affect turnover
Overview
Problem
Job satisfaction changes with many variables, and it is worth measuring before it leads to exits or underperformance.
Approach
I built a Bayesian model that estimates the probability of cases below threshold and shows the result in an app.
Outcome
The project helps prioritize follow-up and preventive actions.