Risk Data Scientist - Risk Management @ING Bank

About the role

You will join a collaborative, forward-thinking team where analytical rigor meets innovation. We work with large datasets, modern tools, and advanced methodologies, including machine learning and AI, to extract meaningful insights and drive impactful decisions. Our team thrives on open communication, knowledge sharing, and continuous learning. We partner closely with colleagues across Risk, Business, IT, and Model Validation functions to ensure that our models are not only technically robust but also aligned with real business needs. Your day-to-day In this role, you will support the full lifecycle of IFRS9 and Credit Decision models for retail, micro-companies, and SMEs. Your responsibilities will include: Developing and calibrating models end-to-end, from scope definition and data collection to estimation and documentation Supporting the implementation of models in internal systems Monitoring model performance, interpreting results, and proactively suggesting improvements Ensuring compliance with internal governance frameworks and methodologies Preparing for independent model validation processes and addressing findings in a timely manner Contribute to defining optimal cut-off strategies for Credit Decision Models, balancing risk and acceptance Perform recurring and ad-hoc portfolio analysis to identify both opportunities and high-risk segments Support business initiatives by selecting and analyzing client data for targeted campaigns Ensure data integrity and proper data management in line with credit risk policies Automate scripts and document workflows to improve efficiency and reliability Apply advanced statistical techniques, including machine learning and AI, on complex datasets Participate in global projects aligned with the bank's strategic priorities What you bring to the team We're looking for someone curious, analytical, and eager to make an impact. Education & experience Degree in Mathematics, Statistics, Cybernetics, or a related field Fluent in English (written and spoken) Experience in model development or validation is a plus Technical skills SAS, SQL (Microsoft/Oracle), Python Microsoft Office tools Familiarity with Azure DevOps Understanding of lending markets and banking regulations (both Romanian and European) Personal competencies Ability to see the bigger picture and make well-balanced decisions Strong organizational, planning, and prioritization skills Analytical thinking and problem-solving mindset High attention to detail and accuracy Proactive attitude, energy, and adaptability in complex environments Strong communication and influencing skills Emotional intelligence and collaborative mindset