Data Scientist (Applied ML & Recommendations)
Tasks
- Build production ML models and pipelines
- Collaborate on engineering decisions from insights and requirements
- Design scalable recommendation infrastructure
- Develop data pipelines with DBT and Databricks
- Maintain production recommendation infrastructure
- Measure and maintain recommendation quality
- Monitor model health and detect drift
- Research and prototype recommendation algorithms
Perks/Benefits
- Company events
- Flexible expense management
- Health insurance
- Home office setup support
- Language classes
- Meal allowances
- Paid training and books
- Remote work options
- Stock options
- Visa sponsorship
Skills/Tech-stack
A/B | A/B Testing | AWS Lambda | AWS SageMaker | AWS Step Functions | Airflow | Amazon ECS | B testing | CI/CD | Contextual Bandits | DBT | Dagster | Databricks | Drift Detection | Git | Graph-Based Recommendations | Graph-based | Learning algorithms | Learning-to-Rank | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Neural Networks | Prefect | Python | SQL | Session-Based Recommendations | Step Functions | Transformers
Education
N/A
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