Lead Data Scientist (Fraud)

TL;DR

Lead Data Scientist (Fraud): Building and deploying ML models to protect hirify.global’s customers from fraudulent activities with an accent on account takeover or identity theft fraud. Focus on exploring novel ML/AI products to detect fraud and communicating with stakeholders on conceptual design, development, deployment, and risk control of the model.

Location: Milan

Salary: €63,236 - €90,429 EUR

Company

hirify.global is a company.

What you will do

• Build and deploy ML models to protect hirify.global’s customers from fraudulent activities.
• Lead data science projects, from problem definition until deployment.
• Monitor, maintain, and retrain existing ML models in production.
• Explore, engineer, and test new potential features to help models in predicting fraud.
• Communicate with stakeholders on conceptual design, development, deployment, and risk control of the model, including writing documentation for external parties.
• Maintain the engineering platform/system used by the team to stay compliant with the company’s requirements.

Requirements

• Have an advanced degree (Master or Doctorate) in a quantitative field (e.g. statistics, computer science, engineering, mathematics, physics, or related fields).
• 5+ years of experience as a Data Scientist, ML Engineer, or related roles in the financial sector.
• 2+ years of experience working in fraud-related problem space.
• Experience in handling large sizes of customer data (e.g. >100 millions transactions with a few hundreds features).
• Deep proficiency in ML end-to-end process: conceptual design, model development, deployment in production, and monitoring, including pitfalls and tradeoffs to make.
• Strong Python and SQL skills, including familiarity with ML modeling packages (e.g. scikit-klean, LGBM) and CI/CD or deployment tools (e.g. Docker, Jenkins, and uv).

Nice to have

• Experience working in payment-related business, e.g. BNPL, credit card, or P2P transfer.
• Technical experience on utilizing Gen AI, Graph Networks, Anomaly Detection, or Behavioral Biometrics into production.
• Familiarity with AI productivity tools for coding, e.g. Cursor or Github co-pilot.
• Familiarity with compliance and regulation around personal data privacy and model bias.
• Experience in mentoring junior data scientists.

Culture & Benefits

• Willingness to collaborate across different locations and time-zones (US and EU), but you will be working at common office hours in your time-zone.
• Traveling for one or two weeks per year may be needed to meet in-person with other group members.
• Eager to take ownership of a project and deliver results with minimal supervision.
• Agile to adapt to new changes in technology or engineering platforms used by the company.