Description

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

Education

Any Graduate