Job Description
4+ years of experience in Model Development / Deployment using Python / R
Good Hands-on knowledge of SQL, Pandas, SKLearnGood understanding of basics of Statistics / Machine Learning
Good understanding of GLM methods, Hypotheses testing, missing data analysis, outlier detection
Ensemble methods ( Random Forests / XGBoost / AdaBoost)
Clustering algorithms - KMeans, KMediods, DBSCAN
Comfortable with generating high quality visualizations with Matplotlib, Seaborn
Strong presentation / Storytelling skills
Familiarity with Dimensional Modeling techniques (Facts / Dimensions / Surrogate Keys)
Familiarity with PowerBI / Tableau highly preferred.
Knowledge of Time Series Forecasting methods preferred
Actuarial background / experience preferred
Any Graduate