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Qualifications

• very good knowledge of Spark and Python
• hands‑on experience building complex data pipelines
• good understanding of ML model deployment and consumption patterns
• ability to refactor, maintain, debug existing machine learning solutions
• problem‑solving skills, being able to troubleshoot and optimize ML models
• interest in banking and banking products
• experience working in international, cross‑functional teams
• knowledge in Airflow, Azure pipelines

Responsibilities

• develop and maintain a code base that produces ML models
• improve data flow, establish new data sources and deployment
• troubleshoot data issues, providing robust solutions to ensure optimal performance and reliability
• continuously optimize our systems for performance and cost‑effectiveness
• document technical specifications, procedures, and outcomes
• use Azure DevOps for CI/CD, task tracking, version control, and other DevOps practices

Team and culture

You will be part of an international highly skilled team of data scientists, machine learning and data engineers (Center of Excellence Analytics Engineering at ING). You will be working in an agile environment helping ING to achieve its goals on a global scale. Your product squad is delivering modern credit engine solution, which provides scoring for B2B lending – they have appetite to grow and expand to deliver solution in multiple countries. You will have opportunity to grow and implement your analytics ideas!

Job details

• Seniority level: Mid‑Senior level
• Employment type: Full‑time
• Job function: Other
• Industries: Banking, Information Services, and Financial Services

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