IM
Insurance → ML Engineering
Claims adjuster applying risk-scoring instincts to ML models
Claims adjuster applying risk-scoring instincts to ML models
Verified Domain Engineer (Beta)
Engineering Depth 5/5
Pivot Story
“Claims adjusting is really about spotting patterns in incomplete information. ML engineering is the same problem with better tools.”
Healthcare
Insurance
The Past
Jan 2011 - Jun 2019 (8 years 5 months)
Claims Adjuster
Adjusted commercial property and casualty claims averaging 200 open cases. Identified a subrogation pattern that recovered 1.4M annually.
The Now
Jan 2020 - Present (6 years 3 months)
ML Engineer
Developing fraud-detection and risk-scoring ML models for an insurtech startup. Python, scikit-learn, and XGBoost. Models in production scoring 50K claims daily.
About
Processed thousands of property and casualty claims. That pattern-recognition instinct now drives the fraud-detection models I build and ship.
Domain Signals
Domain Focus
Insurance
Tech Focus
ML Engineering
Engineering Depth
Level 5/5
Self-rated hands-on software depth.