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Customer Data SME

Cube
CompanyCube
CategoryData & Analytics
LocationLondon
RemoteHybrid
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted1 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.    Why us? 🌍 CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally. 🚀 In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead. 🌱 We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one. 🌐 With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success. 💡 We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance. Role Mission This role provides senior expertise in Operational Risk and Risk Controls, applying it through customer data processing and analysis, ensuring data quality, governance, and strategic utilisation. It develops data standards, advises on complex data challenges, utilises and implements AI solutions and supports major customer initiatives within CUBE. The role mentors junior team members and shapes customer data practices. Key Responsibilities - Actively contribute to CUBE’s success by supporting the delivery of the Data & Analytics team’s goals. - Play a leading role in the execution of all aspects of Customer Data Operations on a prioritised basis. Specifically: - Matching of risks and controls - Index build - Index management - Other data expansion - Contribute to the consistent application of CUBE’s Data Technical Standards to core risk and control content and beyond. - Contribute to the ongoing development of CUBE’s business rules which form the basis for CUBE’s index assets. - As someone with subject matter expertise, contribute to data processing exercises on a prioritised basis as required (particularly matching and index building). - Actively seek opportunities to engage with the rest of D&A (and wider CUBE as appropriate) to improve data and processes - Collaborate closely with other members of the D&A team to support cross-team working and understanding. - Actively support the CUBE-wide objective to automate. Collaborating with CUBE’s Product, Engineering, and Data Science teams to facilitate faster and better data processing. - Leadership and mentorship of more junior members of the team, supporting their development in line with business needs.   Skills & Competencies - Data Management & Quality: Oversees enterprise-wide data architecture and governance practices. Ensure consistency, reliability, and traceability in data assets. - Risk & Governance: Acts as subject matter expert on governance, risk, and compliance. Embeds control standards across operational processes. - Tools, Automation & AI: Leads automation and integration initiatives, embedding AI/ML where relevant. Establishes tool standards and governance. - Problem-Solving & Innovation: Champions innovation in automation and process optimization. Promotes continuous improvement and data-driven decision-making.
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