Data Analytics Engagement Supervisor
Tasks
- Apply causal inference and uplift modeling
- Communicate analytical findings to technical and non-technical audiences
- Deploy and monitor machine learning models
- Develop predictive and prescriptive customer models
- Drive marketing measurement and experimentation
- Lead customer modeling teams for CLV
- Manage full model lifecycle end to end
- Partner with data engineering and platform teams for scalable access
- Provide model design and code review oversight
- Translate business questions into analytical problems
Perks/Benefits
- Adoption expense reimbursement
- Back-up child care
- Dental insurance
- Employee resource groups
- Fertility treatments
- Flexible family care days
- Health insurance
- Paid Holidays
- Paid parental leave
- Paid time off
- Prescription Coverage
- Tuition assistance
- Vehicle discount program
- Vision insurance
Skills/Tech-stack
Causal Inference | Customer Lifetime Value | Data Engineering | Experimentation | Lifetime Value | MLOps | Machine Learning | Marketing measurement | Model Monitoring | Predictive Modeling | Python | SQL | Series forecasting | Statistical Methods | Time Series | Time Series Forecasting | Uplift Modeling
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Analytics | Analytics Manager | Data Science | Data Science Manager | Manager
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