Fraud Operations Data Analytics Associate - Firmwide Operations
Posted on Jan 24, 2019 by Morgan Stanley USA
Operations is one of the largest divisions in the firm and has diverse responsibilities, including correctly settling and recording millions of transactions per day, identifying and mitigating all operational risks, developing strong client relationships and partnering with technology to realize the full potential of IT and e-solutions. Throughout, the Operations department continually seeks ways to improve while actively supporting the development of new businesses, structures and markets.
Firmwide Operations includes Fraud Operations, Shared Services and Banking Operations (SSBO), Operations Risk and Control, Global Project Group and Metrics, Branch Operations, and Divisional Management. Fraud Operations is a global organization responsible for assessing, mitigating, and preventing fraudulent activities across multiple product lines and services in order to protect the firm and its clients.
In an effort to protect our clients' assets, provide a safe and secure banking environment, and to minimize financial losses to the Firm from systematic security risk, the Fraud Operations Team is tasked with monitoring and analyzing client activities in order to detect and curtail fraud. The Fraud Operations Team's primary responsibilities are the identification, mitigation, and incident management of potential fraudulent banking transactions detected by a suite of detection tools, and the expeditious investigation and resolution of client initiated fraud claims.
The global team is expanding and is seeking an associate with skills in business analytics and data science 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 clustering and classification 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.
- Identify emerging fraud trends and recommend appropriate mitigation strategies
- Regularly assess strategy performance including false positive rates and recommend revisions to balance fraud loss vs client disruption
- 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
- 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
- Forge relationships across divisions, including Information Technology, Legal & Compliance, Operations, Credit, and Finance to assist in the implementation of fraud remediation initiatives
- Degree in Computer Science, Engineering, Mathematics, Statistics, Finance, or related quantitative field or equivalent
- In depth knowledge of using MS Office, specifically Excel for basic data analysis and PowerPoint for presentations
- Experienced in SQL for data mining and data wrangling
- Proficiency using Python and Scala to perform data analysis
- Strong quantitative and problem solving skills; proficiency working with large datasets, data mining, statistical methods, segmentation method, algorithm design and implementation
- Strong verbal and written communication skills; ability to act as a bridge between several business areas
- Ability to analyze large, complex, multidimensional datasets with a variety of tools
- Ability to deal with ambiguity and define approaches to bring unfocused issues to resolution
- Strong sense of ownership and accountability for work
- Ability to work independently and in a team environment, build and maintain a network of contacts, and coordinate with a large number of stakeholders across the business and technology
- Experience of Finance, Banking, Insurance or similar businesses a strong plus
- Knowledge of the financial crimes industry
- Knowledge of Hadoop data environment and statistical and visual analytics tools such as SAS, R and Tableau Fraud Operations Data Analytics Associate - Firmwide Operations