Staff Data Scientist - RiskOS

📋 Description

• Develop analytics on RiskOS data to identify fraud patterns.
• Architect scalable data pipelines and ML workflows for batch and streaming.
• Lead design and analysis of experimentation frameworks to optimize workflows.
• Lead GenAI solution creation and evaluation to power analytics and case tools.
• Define GenAI evaluation frameworks, offline benchmarks, safety checks.
• Partner with platform/engineering to build data science infra and tools.

🎯 Requirements

• Master's or PhD in CS/ML or equivalent.
• 6+ years in data science or ML with risk/fraud focus.
• Production GenAI/LLM experience (apps/agents).
• Python and SQL; ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch.
• Build scalable data pipelines and production ML deployments; streaming.
• Databricks, Spark, PySpark, BigQuery.
• Data engineering: ETL, warehousing, schema design, distributed computing.
• Cross-functional collaboration and stakeholder communication.