Applied Machine Learning Lead
Tasks
- Analyze interpret experimentation results
- Collaborate with product developers and commercial teams
- Communicate insights to technical and non-technical stakeholders
- Define experiments hypothesis design and validation
- Design build deploy production machine learning models
- Drive machine learning platform and team continuous improvement
- Establish data science technical standards and documentation
- Lead advanced business analytics
- Lead and coach data science team
- Maintain model reliability testing observability
- Manage data science backlog and roadmap
- Monitor model performance and data drift
- Own end to end experimentation lifecycle
- Review validate challenge models and experiments
- Translate business problems into measurable initiatives
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Apache Spark | Azure | B testing | Causal Inference | Cloud Computing | Code review | Databricks | Experimentation | Feature Engineering | Google Cloud | Hypothesis Testing | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model Validation | Model retraining | Predictive Analytics | Python | SQL | Software testing | Statistical modeling | Version control
Education
N/A
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