Senior Data Scientist – Fraud Detection & AI Application
Tasks
- Architect real time risk and fraud systems
- Build and evaluate ML prototypes and back tests
- Build distributed data pipelines for transaction data
- Communicate modeling choices and interpretability
- Conduct code reviews and system design discussions
- Design agentic AI systems using LLMs and RAG
- Lead end to end machine learning lifecycle
- Perform exploratory data analysis and anomaly detection
Perks/Benefits
Skills/Tech-stack
AWS | Anomaly Detection | Data Modeling | Databricks | Experimentation | Fraud Detection | GCP | LLM | MLflow | Machine Learning | Python | RAG | Risk scoring | SQL | Scikit-learn | Threat Intelligence | XGBoost
Education
Roles
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