Distribution Client Data Analyst

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Skills you'll use

What you'll do

• Client data sourcing and data quality: Validate transaction data by coordinating with external vendors, maintain client data across internal platforms, monitor data quality trends, identify issues, perform root-cause analysis, and develop remediation plans to improve accuracy, completeness, reliability, and usability of governed data assets.
• Data Governance and metadata: Act as business owner of client data, maintain business glossaries, reference data repositories, metadata attributes and governed data elements.
• Commercial insight enablement: Support Sales and Client Service managers with data-led insights that improve client acquisition, retention, expansion and day-to-day commercial engagement, strengthening decision-making across EMEA Distribution.
• Cross-functional delivery: Act as the point of contact between Distribution, Data Governance, Technology, wider data teams, senior leadership and business stakeholders – resolving operational roadblocks and increasing confidence in data.

Who can apply

• Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Business Analytics or a related discipline.
• Data management and governance: Experience in data quality, data governance, master data management, business data management, metadata management, taxonomy, or process design.
• Technical capability: Strong SQL and Python skills required for data analysis, workflow automation, and quality checks.
• Commercial data experience: Experience with diverse datasets (preferably distribution) within financial services, asset management, or wealth management preferred.
• CRM platforms: Experience working with CRM platforms, preferably Salesforce, with an understanding of how client and account data supports sales coverage, engagement and reporting.
• Asset management data domains: Exposure to AUM, flows, client hierarchies, funds and products, mandates, distribution platforms and transfer agency data.
• Analytical judgment: Strong problem-solving skills with the ability to analyze large datasets, identify patterns, interpret results, and convert findings into actionable insight.
• Communication and influence: Ability to explain complex data concepts clearly to business and technical audiences and translate data into commercial recommendations.
• Execution and collaboration: Organized, proactive, and comfortable managing multiple priorities while working independently and across global, cross-functional teams.
• Tools: Strong working knowledge of Microsoft Office (particularly Excel) and AI assistants such as Copilot .

About Ameriprise Financial

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