Director, Data Science/ML
Tasks
- Build and deploy machine learning models for product use cases
- Build dashboards and monitoring systems
- Build mentor and scale data science team
- Build personalization and recommendation systems
- Collaborate with analytics engineering on model deployment and monitoring
- Conduct user behavior analysis for product optimization
- Define and execute product data science strategy
- Define measurement frameworks and success metrics
- Design and implement experimentation frameworks
- Develop causal inference methods
- Own end-to-end machine learning lifecycle
- Partner with product engineering and UX leadership on roadmap
Perks/Benefits
- ChatGPT access
- Claude access
- Cookunity credits
- Fitness subsidies
- Flexible paid time off
- Paid compassionate leave
- Paid family leave
- Paid sabbatical
- Personalized Spanish Coaching
- Stock options
- Wellness subsidies
Skills/Tech-stack
A/B | A/B Testing | AWS | Apache Airflow | B testing | Causal Impact | Causal Inference | Experimentation | Feature Engineering | Feature Stores | GCP | Kubeflow | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model Deployment | Model Monitoring | Personalization | Predictive Modeling | Production Machine Learning | PyTorch | Python | Real Time | Real-time ML | Recommendation Systems | SQL | Scikit-learn | Snowflake | TensorFlow
Education
Bachelor of Science | Master of Engineering | Master of Science | PhD
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