An ideal candidate needs to be an expert with the following techniques and tools:
- Independently explore and research in the area of Time Series forecasting.
- Comfortable to build models in R/Matlab/SAS/Python/C++ and validate hypothesis based on available data.
- Expertise in one or more modeling/machine learning platforms as such as R, SAS, and Python.
- Hands on experience in Classification methods (e.g., Neural Net, Logistic Regression, Decision Trees, KNN, SVM, Random Forest)
- Strong exposure to the Regression methods (e.g., Linear, Nonlinear, Boosted Regression Trees )
- Hands on experience in Time-series Modeling/Forecasting (e.g., AR, ARMA, GARCH, Exponential Smoothing)
- An expert in Statistical Analysis (e.g., Hypothesis Testing, Experiment Design, Hierarchical Modeling, Bayesian Inference)