Customer Data Scientist

The role

You will tune and optimize detection models and thresholds for customers using live transaction data. You will investigate detection performance and present technical findings to customer stakeholders.

What you will do

• Tune and optimize detection models and thresholds against live transaction data.
• Investigate detection performance including missed cases, alert quality, and pattern drift.
• Translate technical findings into customer-facing insight.
• Present findings and defend methodology directly to customers.
• Partner with regional Customer Value Partners on account strategy.
• Feed patterns and findings back into broader model and product functions.
• Own the regulatory defensibility of tuning decisions through documentation.
• Validate model changes using backtesting, sample review, and sign-off discipline.

Required qualifications

• 5-7 years as a data scientist in a customer-facing role.
• Experience presenting analysis and defending model decisions directly to clients.
• Real experience in AML, fraud detection, or financial crime analytics.
• Strong hands-on skills in Python and SQL.
• Experience with ML tooling used in production.
• Ability to be the technical voice in rooms with risk, compliance, or data science stakeholders.
• Track record of translating model performance into business value for non-technical stakeholders.
• Comfort with ambiguity and live production systems.
• Ownership mentality.

Nice to have

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

About the company

Hawk is the leading provider of AI-supported anti-money laundering and fraud detection technology. They offer a culture of mutual trust, support and passion.