Hybrid Data-Driven Risk Analytics Lead

SmartRecruiters, Inc.; Amsterdam; Hybrid; EUR 90,000 - 120,000; Full time

Job summary

Riverty in Amsterdam is seeking a Lead for a Risk Analytics team to drive data-driven insights on solvency and fraud indicators within a balanced risk environment. You will shape risk strategy, develop analytics and monitoring, and collaborate with Risk Product, Steering, Data Science, Pricing, and Finance to optimize outcomes.

The role requires 3+ years leading cross-border risk analytics teams, strong SQL/Python skills, and experience deploying ML-based risk models in an international setting.

Qualifications

• Proven track-record in data analytics and credit risk management.
• 3+ years leading cross-border teams in credit risk analytics.
• Experience enabling machine learning-based models and advanced analytics for risk assessment.
• Proficiency in SQL and Python for complex analytics tasks.
• Strategic thinker with strong execution and collaboration across functions.
• English required; German or Dutch a plus.

Responsibilities

• Lead a high-performing risk analytics team in an international setup.
• Use analytics tools and data-driven decision-making to solve fraud/ solvency risk problems.
• Drive improvements in data analyses, processes, and monitoring with best practices.
• Provide risk insights for pricing requests and collaborate with stakeholders.
• Enable machine learning models and advanced analytics for risk decisioning.
• Represent the team in projects with analytics and implementation responsibilities.

Skills

Data analytics

Team leadership

SQL

Python

Machine learning

Risk management

Job description

Riverty in Amsterdam is seeking a Lead for a Risk Analytics team to drive data-driven insights on solvency and fraud indicators within a balanced risk environment. You will shape risk strategy, develop analytics and monitoring, and collaborate with Risk Product, Steering, Data Science, Pricing, and Finance to optimize outcomes.

The role requires 3+ years leading cross-border risk analytics teams, strong SQL/Python skills, and experience deploying ML-based risk models in an international setting.