Design and improve fraud detection systems that prioritize high-risk claims
Collaborate across teams and functions, working closely with fraud analysts, engineers, and product managers
Develop deep expertise in fraud dynamics, identifying emerging fraud patterns and translating insights into effective detection and prevention strategies

At least 3 years of experience in analytical fraud detection in the Insurance, Finance or Law Enforcement domain
Applied knowledge of network analysis, anomaly detection or risk scoring and segmentation to real fraud problems
Strong Python programming skills, especially in the data domain, and fluent use of Git
Knowledge of Spark, SQL or any other data-oriented programming language
Proficiency with standard data wrangling and modeling libraries (Pandas, Sklearn, Keras, XGBoost, LightGBM, etc.)
Nice-to-Have: Experience in motor insurance
In-depth knowledge of graph databases (Neo4j, AWS Neptune) and analytics (NetworkX, GNN) or explainability applied to anomaly detection
Knowledge of BI tools (Tableau or similar)
Proficiency in Italian and/or Spanish.

Senior Data Scientist – Fraud

Key skills