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Senior/lead data scientist-fraud (turbigo)

Turbigo
Klarna
Data scientist
Pubblicato il Pubblicato 23h fa
Descrizione

Responsibilities

Sebbene l'esperienza qualificato e le qualifiche siano fondamentali per questo ruolo, si assicuri di verificare di possedere le soft skill preferenziali, se richieste, prima di candidarsi.

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- 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 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.
- Proactive in exploring novel ML/AI products to detect fraud.

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 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.
- 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 hand

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