Data Scientist – Retail Analytics
Wellesley-93 Worcester St, United States
USD 86K-173K Mid-level Full Time
Tasks
- Assess competitive environments
- Build causal inference models
- Build predictive models for pricing and promotion
- Collaborate with technical and non-technical stakeholders
- Deploy machine learning solutions using MLOps practices
- Develop econometric pricing models
- Develop scalable deployment ready machine learning models
- Evaluate model performance and statistical validity
- Implement model monitoring and data drift monitoring
- Measure customer impact of pricing and promotions
- Optimize code for large datasets
- Present analytics insights and recommendations
- Simulate pricing and promotional decisions
- Translate business requirements into testable hypotheses
Perks/Benefits
- Dental insurance
- Medical insurance
- Paid time off
- Retirement savings options
- Vision insurance
- Wellness programs
Skills/Tech-stack
AWS SageMaker | Bayesian hierarchical modeling | CI/CD | Causal Impact | Causal Inference | Cross Effects | Databricks | Deep learning | Difference-in-differences | Econometrics | Generative AI | Git | Hierarchical modeling | Kubeflow | MLOps | Machine Learning | NLP | Price elasticity | Pricing Analytics | Promotion Lift | Propensity Score Matching | Propensity score | Python | Retail Analytics | SQL | Score Matching | Series forecasting | Synthetic controls | Time Series | Time Series Forecasting | Version control | Vertex AI
Education
Roles
Regions
Countries
States
Cities
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