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Data Analytics Lead Wealth Management and Investment Management
Morgan Stanley USA
February 10, 2018
New York, New York
Morgan Stanley is seeking a strong Data Analyst Lead to support Wealth Management and Investment Management Audits. The candidate will be the primary point of contact for financial and technology auditors for the extraction, analysis, and testing of controls.
The Data Analyst Lead for Wealth Management and Investment Management will manage multiple audit assignments, help determine the scope of analytics work, and drive the completion of the testing by coordinating with technology teams and audit colleagues. Candidate must have strong communications skills and comfortable working on unstructured assignments where scope is not always defined upfront. In addition, the candidate should demonstrate the ability to understand complex technology infrastructure as it relates to data flows and business processes. Candidate will drive innovation in the use of data analytics in Wealth Management audits, including the use of Big Data for exploratory data analysis, outlier detection, and risk identification. The DA Lead will work with auditors to understand key processes and risks and provide suggestions on where data analytics can be applied to increase the coverage of audit execution and achieve efficiencies through automation. Additionally, the Lead Data Analyst will work with the team to create repeatable tools that enable the audit team to reuse across multiple audits.
"Skills Required: - Strong SQL and knowledge of data extraction and manipulation techniques including the ability to stage and import large volumes of data. - Ability to work with multiple sources of disparate data - Working knowledge of Big Data environments including Teradata - Technical knowledge of data models and database design - Ability to present complex information in an understandable and compelling manner -Strong communication skills and ability to thrive in a fast paced, multiple deliverables, team-oriented environment - Understanding of Wealth Management and Investment Management business and products Desired Skills: - Familiarity with SAS, Mainframe -Working knowledge of tools for data analysis, including R, Python, or business intelligence products such as Qlikview, Tableau, etc. "