Staff Data Scientist (Fraud & Risk)
Tasks
- Build and deploy generative AI and agentic AI workflows for fraud investigation
- Build model performance metrics and report insights to stakeholders
- Deploy models and implement CI CD pipelines
- Design predictive machine learning models for fraud detection and risk assessment
- Detect and resolve data drift and concept drift in production pipelines
- Handle imbalanced datasets using sampling and cost sensitive learning
- Implement model tracking and observability
- Optimize feature engineering for real time and batch fraud decisioning
Perks/Benefits
- Generous annual leave
- Home office setup
- Laptop ownership
- Learning and development budget
- Mental wellbeing support
- Parental leave
- Private health insurance
- Sabbatical
- Volunteering and development days
- Work from abroad
Skills/Tech-stack
AWS Bedrock | Adversarial Models | Agentic AI | BigQuery | CI/CD | Cloud Computing | Concept drift | Data Drift | Databricks | Ensemble learning | Feature Store | Fiddler | Fraud Detection | GenAI | Hadoop | Hugging Face | Imbalanced Learning | Langgraph | LightGBM | Machine Learning | Model Observability | PyTorch | Python | Random Forest | SQL | Snowflake | Spark | Support Vector Machines | Synthetic data | Tecton | Vector machines | XGBoost
Education
N/A
Roles
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