Data Scientist

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

This role tunes anti money laundering and fraud detection models on live customer transaction data, weighing detection gains against alert volume. A strong candidate has several years of customer facing data science work in financial crime, can dig into missed cases and pattern drift, and can explain and defend tuning choices to compliance teams and regulators. Judgment about when a model change is safe matters as much as technical skill.

How it fits the AI era

The models here blend rules with explainable AI, so the work is less about building models from scratch and more about adapting and justifying them on real data. AI speeds up analysis and pattern finding, but explaining why an alert fired and standing behind that reasoning with a customer stays human. Regulatory defensibility and sign off discipline remain firmly in people's hands.

How it builds AI experience

Working on explainable detection models for banks, payment firms and crypto companies builds practical skill in tuning AI systems under real compliance constraints. A candidate can strengthen this by studying transaction monitoring typologies, false positive economics, and how hybrid rules plus AI detection is validated and documented for audits.

Worth showing

• AML or fraud analytics
• Customer facing data science
• Python and SQL
• Model and threshold tuning
• Explaining models to stakeholders

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Hawk AI

Hawk provides AI-powered anti-money laundering, screening, and fraud prevention technology for banks, payment companies, neobanks, fintechs, and cryptocurrency firms, per the company.