Data Scientist
Tasks
- Architect marketing data science roadmap
- Build media mix modeling solutions
- Build user lifetime value models
- Collaborate with marketing leadership on data integration
- Conduct causal inference analysis
- Create experimental design and analysis
- Deploy, monitor, and maintain models in production
- Design and lead production data science projects
- Design data pipeline architecture
- Develop MLOps tooling and processes
- Develop multi-touch attribution models
- Ensure code rigor and scalability
- Optimize marketing spend engines
- Partner with data engineering on marketing data products
- Prototype emerging marketing models
- Provide technical mentorship for data scientists
- Set modeling quality standards
Perks/Benefits
- Career coaching support
- Fitness benefits
- Hybrid work schedule
- In-office culinary options
- Inclusive family building benefits
- Mental health & wellness benefits
- Retirement plans
Skills/Tech-stack
Amazon Redshift | Apache Spark | Causal Inference | Experimental Design | Lifetime Value | MLOps | MLflow | Machine Learning | Media mix modeling | Mix Modeling | Multi-Touch Attribution | Multi-touch) | Python | R | SQL | Statistical modeling | User Lifetime Value
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Regions
Countries
States
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