Data Scientist

Dashly; Deutschland; Remote; EUR 50.000 - 75.000; Vollzeit

Zusammenfassung

A leading tech company in Germany is seeking a Data Scientist to apply statistical analysis and machine learning to detect fraud and assess labor risk. The ideal candidate will have strong problem-solving skills and experience in fraud detection, risk modeling, or related areas. This role involves collaboration across teams to align data initiatives with business goals and bring solutions into production.

Qualifikationen

• Experience in fraud detection.
• Experience in risk modeling.
• Experience in identity mapping.
• Experience in entity resolution.

Aufgaben

• Design and implement statistical models and machine learning algorithms to detect fraudulent patterns.
• Analyze large-scale datasets to derive actionable insights.
• Work cross-functionally with leadership and engineering.
• Collaborate with product teams for production.
• Apply thoughtful experimentation and model evaluation techniques.

Kenntnisse

Statistical analysis

Machine learning

Problem-solving

Communication skills

Jobbeschreibung

As a Data Scientist, you’ll work at the intersection of data and engineering, applying statistical analysis, machine learning, and thoughtful experimentation to uncover fraud and assess labor risk. You should be comfortable working at the intersection of data and engineering, with a strong problem-solving mindset and excellent communication skills. Bonus points if you have experience in fraud detection, risk modeling, identity mapping, or entity resolution.

What you'll do:

• Design and implement statistical models and machine learning algorithms to detect fraudulent patterns.

• Analyze large-scale datasets to derive actionable insights for internal and customer-facing applications.

• Work cross-functionally with leadership, engineering, and users to align data initiatives with business goals.

• Collaborate closely with engineering and product teams to bring data science solutions into production.

• Shape the intelligence layer of our platform by applying thoughtful experimentation and model evaluation techniques.