Data Scientist
Tasks
- Apply statistical methods and causal inference
- Architect scalable data strategies and governance
- Build Data Integration solutions
- Build end-to-end machine learning systems
- Conduct experimentation using A B testing and MABs
- Design predictive models
- Develop deep learning models for unstructured data
- Implement MLOps pipelines and model deployment
- Lead AI governance and evaluation standards
- Lead rapid prototyping for validation
Perks/Benefits
- Collaborative work environment
- Direct access to AI platforms
- Diverse and inclusive culture
- Growth opportunities
- Hybrid working model
- Supportive leadership
Skills/Tech-stack
A/B | A/B Testing | AI Governance | AWS SageMaker | Apache Spark | Azure ML | Azure ML Services | B testing | Bayesian Methods | Causal Inference | Computer Vision | Data Governance | Data Quality | Data Warehousing | Data integration | Deep learning | Docker | Experiment design | GCP Vertex | GCP Vertex AI | Hadoop | Kubeflow | Lakehouse | Language Processing | ML services | MLOps | MLflow | Machine Learning | Multi-Armed Bandits | Natural Language | Natural Language Processing | NumPy | Pandas | Python | R | Statistical modeling | Survival analysis | Vertex AI
Education
Roles
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