AML & Fraud Data Scientist: Explainable AI Tuning

present of AI; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Hawk AI is seeking a data scientist with AML and fraud analytics experience to tune detection models using live transaction data. You will balance gains in detection with alert volumes and ensure regulatory defensibility, while explaining tuning decisions to compliance teams and regulators.

Ideal candidates have several years of customer facing data science work in financial crime, with strong Python and SQL skills and a track record of addressing missed cases and drift in production models.

Qualifications

• Several years of customer facing data science work in financial crime.
• Ability to analyze missed cases and pattern drift.
• Ability to explain and defend tuning choices to compliance teams and regulators.

Responsibilities

• Tune anti-money laundering and fraud detection models on live transaction data.
• Balance detection gains against alert volume and regulatory defensibility.
• Explain tuning choices to compliance teams and regulators.
• Investigate missed cases and pattern drift to improve models.

Skills

AML analytics

Customer facing data science

Python

SQL

Model tuning

Stakeholder communication

Tools

SQL

Jupyter

Job description

Hawk AI is seeking a data scientist with AML and fraud analytics experience to tune detection models using live transaction data. You will balance gains in detection with alert volumes and ensure regulatory defensibility, while explaining tuning decisions to compliance teams and regulators.

Ideal candidates have several years of customer facing data science work in financial crime, with strong Python and SQL skills and a track record of addressing missed cases and drift in production models.