Data Scientist
Tasks
- Apply probabilistic and Bayesian modeling
- Design machine learning models for business use cases
- Develop and evaluate model performance metrics
- Develop reproducible documented code and notebooks
- Engineer features and wrangle data
- Monitor model degradation and recommend retraining
- Perform exploratory data analysis
- Translate business questions into statistical problems
Perks/Benefits
- Collaborative culture
- Multicultural experience
- Professional growth
- Structured learning and development programs
Skills/Tech-stack
A/B | A/B Testing | AWS Lambda | AWS SageMaker | Amazon ECS | B testing | Bayesian Inference | CatBoost | Causal Inference | Clustering | Cross-validation | Data Wrangling | Dimensionality Reduction | Feature Engineering | Gradient boosting | LightGBM | Logistic Regression | MLflow | Marketing Mix | Marketing Mix Modeling | Matplotlib | Mix Modeling | Model Evaluation | NumPy | Pandas | Plotly | Prophet | Pymc | Pymc-marketing | Python | Random Forests | SQL | SciPy | Scikit-learn | Seaborn | Series forecasting | Sktime | StatsModels | Support Vector Machines | Survival analysis | 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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