Problem Solver
Benjamin Harlander
Areas Benjamin Harlander is Knowledgeable in:
Predictive modeling with statistical and machine learning methods. Particularly interested in applications involving agriculture and transportation/logistics.
Techniques Benjamin Harlander Uses:
Exploratory data analysis, statistical/machine learning, generalization error estimation, mathematical modeling, linear programming
Benjamin Harlander's Problem Solving Skills:
- Programming in R, SAS, SQL, Python
- Statistical Modeling
- Statistical Inference
- Machine Learning
- Technical Communication
- Linear & Integer Programming
Benjamin Harlander's Problem Solving Experience:
- I created a soybean variety selection procedure using statistical learning and discrete optimization techniques.
- I built a classification model to predict auto insurance claim interactions and increase operational efficiency.
- I built models to predict suspicious (potentially fraudulent) vehicle theft claims using gradient boosting machines and logistic regression. Work involved research of sophisticated sampling techniques for handling class imbalance (rare event occurrence).
- I built random forests and gradient boosting machines to create multi-class predictions for the interest level users may show in new apartment listings.