- Programming: Python (Preferred) / R
- Proficiency in relational databases and SQL querying
- Proficiency in working with Excel / Google Sheets (knowledge of data read & write connectors)
- Deep understanding and experience with implementing of ML models in at least some of the techniques from each of the following buckets:
Regression: Linear, Logistic, Multinomial, Mixed effect
Classification: Bagging & Boosting (Random Forest), Decision tree, SVM
Clustering: K-Means, hierarchical, DB-Scan
Time series: ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM
Neural Networks: RNN, CNN, (Deep learning), Naive Bayes
- Dimensionality Reduction: PCA, SVD, etc.
- Optimization Techniques: Linear programming, Gradient Descent, Genetic Algorithm
- Cloud: Understanding of Azure / AWS offerings, Setting up ML pipeline in cloud
