Qualifications
OVERVIEW
- 25+ Years of Experience in Data Science
- 10+ Years of Experience in Software Development
- 10+ Years Teaching Graduate Level Statistics and Machine Learning
- Pragmatic / Creative Approach
- PhD Engineering – Specialized in Machine Learning and Artificial Intelligence
INDUSTRIES
Experienced in developing models in a wide range of industries and use cases. Experience includes:
Insurance:
- Auto/Life/Business Risk
- Territory Risk
- Usage Based / Telematics
Banking:
- Credit Risk Models
- Loss Given Default
- Prepay Models
- CECL / CCAR
Medical:
- Claims Payment
- Fraud Models
- Health Care Studies
Marketing / Retail:
- Retention / Churn
- Customer Lifetime Value
- Customer Segmentation
- Customer Response
- Store Placement
Other Industries:
- Telecom
- Manufacturing
- Entertainment
- Startup Companies
ANALYTIC TOOLS
Python:
- Scikit
- Tensor Flow
- NLTK
- PySpark
SAS:
- SAS Programming
- SAS Macro Language
- SAS Enterprise Miner
- SAS Forecast Server
Other Tools:
- R Programming
- Amazon Web Services
- SQL
- Tableau
- Data Robot
ANALYTIC TECHNIQUES:
Statistic Techniques
- Generalized Linear Models
- Linear / Logistic Regression
- Ad Hoc Statistical Tests
Machine Learning
- Decision Trees
- Gradient Boosting
- Random Forests
- Deep Learning Neural Networks
- Clustering / Segmentation
- Artificial Intelligence
Other Techniques
- Time Series Analysis
- Natural Language Processing
- Variable Selection / Reduction
- Fractal / Chaos Analysis
