Customer Data Scientist @Hawk

Overview

As a Customer Data Scientist at Hawk, you will work closely with customers to optimize their anti-money laundering (AML) and fraud detection models based on their transaction patterns. This role involves direct engagement with customers to ensure models are defensible and effective.

Key Responsibilities

• Tune and optimize detection models against customers' live transaction data.
• Investigate detection performance, analyzing missed cases and alert quality.
• Translate technical findings into insights for customers, showcasing productivity gains and cost reductions.
• Present findings to customers and defend methodologies in discussions with compliance teams.
• Collaborate with regional Customer Value Partners to inform account strategies.
• Feed findings back into broader model functions at Hawk.
• Ensure regulatory defensibility of tuning decisions with proper documentation.
• Validate model changes through methods like backtesting and sample reviews.

Requirements

• 5-7 years as a data scientist in customer-facing roles.
• Experience in AML, fraud detection, or financial crime analytics.
• Strong skills in Python, SQL, and relevant ML tooling.
• Ability to articulate model performance to non-technical stakeholders.
• Comfort with ambiguity and live production environments.
• Ownership mentality towards detection performance.

Benefits

Details about benefits offered by Hawk are not specified in the listing.

Location

United States

How to Apply

Application details are available on Hawk's careers page.

Deadline

No specific deadline is mentioned.