Compliance Data Methodology Specialist

About the role

ING Hubs Poland is hiring a Compliance Data Methodology Specialist in Warsaw. The role leads the delivery of strategic data initiatives that make Compliance more data-driven, acting as the central point of contact for Compliance data needs and helping unlock the value of data, AI and GenAI to strengthen compliance risk management. The team sits in the Compliance Frameworks & Control department of Group Compliance.

Key responsibilities

• Own and manage a complex Compliance data delivery roadmap and support priority setting.
• Act as the central point of contact for Compliance data requirements and initiatives.
• Discuss and validate data architecture, data exchange agreements and legal documentation needed for data ingestion.
• Present, influence and negotiate Compliance priorities during quarterly planning and governance cycles.
• Identify opportunities to use data to support Compliance risk management and partner with analytics and AI leadership on AI and GenAI opportunities.
• Develop and maintain dashboards and analytical solutions that give actionable business and regulatory insights.
• Lead strategic projects from a data, analytics and governance perspective, and propose solutions to senior stakeholders.
• Drive improvements in data literacy, data capabilities, digitalisation and future technologies, and organise data awareness campaigns and roadshows.

Required profile

• 5+ years of experience in data, analytics or data transformation roles, with a track record of leading complex data change initiatives.
• Experience in Compliance or a strong understanding of Compliance processes and challenges.
• Strong stakeholder management and the ability to influence across functions, countries and organisational levels.
• Fluent English and the ability to build trusted relationships through collaboration and constructive feedback.

Required skills

• Hands-on experience with AI, machine learning and rapid prototyping.
• Proficiency in Python and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow and Dash.
• Dashboards and visualisations in Power BI, Cognos or similar.
• Understanding of data architecture, data governance and data ingestion.