Data Scientist

📋 Description

• Tune and optimize detection models and thresholds against each customer's live transaction data
• Investigate detection performance deeply: dig into missed cases, alert quality, and pattern drift
• Translate technical findings into customer-facing insight
• Present findings, defend methodology to customer's data science or compliance team
• Partner closely with regional Customer Value Partners on account strategy
• Feed patterns and findings back into Hawk's broader model and product functions

🎯 Requirements

• 5-7 years as a data scientist in a customer-facing role, presenting analysis and defending model
• Real experience in AML, fraud detection, or financial crime analytics
• Strong hands-on skills in Python, SQL, and ML tooling in production
• Comfortable being the technical voice in a room with customer's risk, compliance, or data science
• Track record of translating model performance into business value for non-technical stakeholders
• Comfort with ambiguity and live production systems

🎁 Benefits

• Experience in transaction monitoring or payments fraud detection at a bank, payment provider, or
• Familiarity with explainable AI and rules-based hybrid detection approaches