Data Scientist – Dynamic Pricing & Offer Optimization
Tasks
- Build churn propensity and retention uplift models
- Build price elasticity and conversion prediction models
- Collaborate with data engineers on feature store alignment
- Create automated pipelines for model training scoring and retraining
- Design A B testing and uplift modeling
- Develop offer recommendation and ranking models
- Develop pricing simulation engines for scenario testing
- Implement real time feedback loops for model improvement
- Perform clustering and similarity discovery
- Translate insights into business rules and thresholds
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ARPU | B testing | Churn Rate | Clustering | Customer Lifetime Value | Data Visualization | Econometrics | Elasticity | Feature Engineering | Feature Store | K-Nearest Neighbors | K-nearest | Lifecycle Management | Lifetime Value | LightGBM | MLOps | Machine Learning | Model Lifecycle | Model Lifecycle Management | Nearest neighbors | NumPy | Pandas | Python | Reinforcement Learning | Scikit-learn | Statistics | StatsModels | Telecom KPI | Uplift Modeling | XGBoost
Education
N/A
Roles
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