Senior/Lead Data Scientist-Fraud

Klarna; Milano; In loco; EUR 51.000 - 71.000; Tempo pieno

Descrizione del lavoro

A leading financial technology company based in Milan is looking for a Senior Data Scientist specializing in fraud prevention. The ideal candidate will have significant experience in machine learning and will lead projects aimed at safeguarding customers from fraudulent activities. Familiarity with AWS and strong Python/SQL skills are essential for this role. The position offers a competitive salary between €51,328 and €70,825, with opportunities for career development.

Competenze

• 5+ years of experience as a Data Scientist or related role in the financial sector.
• 2+ years of experience in fraud-related problem space.
• Ability to communicate effectively with technical and non-technical roles.

Mansioni

• Build and deploy ML models to prevent fraudulent activities.
• Lead data science projects from definition to deployment.
• Maintain and monitor existing ML models in production.

Conoscenze

Python

SQL

Machine Learning

Data Analysis

AWS Cloud Computing

GitHub

Formazione

Advanced degree in a quantitative field

Strumenti

scikit-learn

Docker

Jenkins

Descrizione del lavoro

Join to apply for the Senior/Lead Data Scientist-Fraud role at Klarna.

What you will do

• Build and deploy ML models to protect Klarna’s customers from fraudulent activities (e.g. account takeover or identity theft fraud).
• 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 predict 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.
• Proactive in exploring novel ML/AI products to detect fraud.

Who you are

• 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.
• Deep understanding of business value to deliver: know when an ML solution is needed and when the model is good enough to be deployed for production.
• Good understanding of what metrics to use for monitoring and when to retrain ML models.
• Strong Python and SQL skills, including familiarity with ML modeling packages (e.g. scikit-learn, LGBM) and CI/CD or deployment tools (e.g. Docker, Jenkins, and uv).
• Familiarity with Github and AWS Cloud Computing (Sagemaker, Lambda, S3, Athena, etc).
• Ability to communicate effectively with Analysts, Engineers, and non-technical roles.
• Strong ability to translate business problems into analytical/technical solutions.
• 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.

Awesome 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 (beyond just prompting, fine-tuning, or proto-typing solutions).
• 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.
• Experience with inferring the outcome of rejected orders due to fraud suspicion or credit unworthiness.

Please include a CV in English.

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Milan, Lombardy, Italy €51,328.00-€70,825.00 16 hours ago

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Software Development