Data Scientist
Tasks
- Apply probabilistic and Bayesian modeling
- Build and evaluate machine learning models
- Design machine learning models
- Detect model degradation
- Develop model performance metrics
- Develop production ready model delivery
- Maintain reproducible documented code
- Perform exploratory data analysis
- Perform feature engineering
- Present findings to technical and non-technical stakeholders
- Recommend model retraining
- Translate business questions into statistical problems
- Wrangle and clean data
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AUC | AWS Redshift | B testing | Bayesian Inference | BigQuery | Calibration | CatBoost | Clustering | Cross-validation | Dimensionality Reduction | ECS | Gradient boosting | Hypothesis Testing | Lambda | Lift Gain Curves | LightGBM | Logistic Regression | MAPE | MLflow | Matplotlib | NumPy | Pandas | Plotly | Prophet | Pymc | Pymc-marketing | Python | RMSE | Random Forests | SQL | SVM | SageMaker | SciPy | Scikit-learn | Seaborn | Series forecasting | Sktime | Snowflake | Statistical Hypothesis Testing | StatsModels | Support Vector Machines | Time Series | Time Series Forecasting | Uncertainty Quantification | Vector machines | WandB | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Technology | Master of Science | Master of Technology
Roles
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