[Hiring] Customer Data Scientist @Hawk

Role Description

As a Customer Data Scientist at Hawk, you're the person our customers trust to make their AML and fraud detection models actually work for them:

• Tuned to their transaction patterns.
• Defensible to their regulators.
• Provably effective in their own numbers.

You sit inside the regional customer team, working directly alongside Customer Value Partners on live accounts. Your work spans:

• Model and threshold tuning.
• Deep analytical investigation into detection performance.
• Building the customer-facing narrative that shows improvements and reasons behind them.

Key Responsibilities

• Tune and optimize detection models and thresholds against each customer's live transaction data.
• Investigate detection performance deeply: analyze missed cases, alert quality, and pattern drift.
• Translate technical findings into customer-facing insights.
• Present findings to customers and defend methodologies.
• Partner closely with regional Customer Value Partners on account strategy.
• Feed patterns and findings back into Hawk's broader model and product functions.
• Own the regulatory defensibility of tuning decisions.
• Validate model changes before they go live through backtesting and sample review.

Qualifications

• 5-7 years as a data scientist in a customer-facing role.
• Real experience in AML, fraud detection, or financial crime analytics.
• Strong hands-on skills in the standard data science stack (Python, SQL, etc.).
• Comfortable being the technical voice in discussions with risk, compliance, or data science stakeholders.
• A track record of translating model performance into business value for non-technical stakeholders.
• Genuine comfort with ambiguity and live production systems.
• An ownership mentality.

Bonus

• Experience in transaction monitoring or payments fraud detection.
• Familiarity with explainable AI and rules-based hybrid detection approaches.