Vice President - Data Scientist - Cyber Data Risk & Resilience Company Profile Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, wealth management and investment management services. With offices in more than 41 countries, the Firm's employees serve clients worldwide including corporations, governments, institutions and individuals. For further information about Morgan Stanley, please visit www.morganstanley.com. Technology & Operations Risk Technology and Operations Risks mission is to deliver first-line defenses to manage Cyber and Fraud risks to Morgan Stanleys technology, operations and information through risk identification, control management and assurance. This allows the business to operate and grow in a secure and legally-compliant manner. The teams vision is to deliver programs that protect and enable the business, ensure secure delivery of services to clients, adjust to address the risks presented by an evolving threat landscape and meet regulatory expectations. Job Profile The global team is expanding and is seeking a leader in business analytics and data scientist to help build out a team to solve data-driven problems to help prevent fraud. The successful candidate should have a deep understanding of business analytics, statistical and predictive modeling concepts, machine-learning approaches, and deep learning techniques. The candidate should be able to solve complex analytical problems using quantitative approaches with a unique blend of analytical, mathematical and technical skills. The candidate should have experience building and managing complex analytic technical architectures. Candidate should be passionate about asking and answering questions in large datasets, and able to communicate that passion to product managers and engineers. The right candidate has (Responsibilities); > Query and mine large data sets to discover transaction patterns, examine financial data and filter for targeted information using traditional as well as predictive/advanced analytic methodologies to proactively identify fraud trends > Preparation of various daily, weekly, monthly and ad hoc reports utilized to drive decisions and measure success > Regularly assess strategy performance including false positive rates and recommend revisions to balance fraud loss vs client disruption > Identify emerging fraud trends and recommend appropriate mitigation strategies Ability to clearly communicate change recommendations based on data-driven analysis > Prepare and document review findings in a concise, understandable manner for written communication to the appropriate parties > Forge relationships across divisions, including Information Technology, Legal & Compliance, Operations, Credit, and Finance to assist in the implementation of fraud remediation initiatives
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