Senior Managers, Risk Management - job 15 of 32

Senior Managers, Risk Management at American Express are crucial in designing and executing business strategies and risk management solutions. They analyze both structured and unstructured data using advanced techniques such as machine learning and financial modeling. Additionally, they collaborate with various teams to implement risk policies and identify new data sources that could enhance profitability. This role really focuses on continuous improvement through the application of best practices and regulatory feedback.

To qualify for the Senior Manager, Risk Management position at American Express, candidates need a Master’s degree in a related field such as Finance, Statistics, or Computer Science. A minimum of one year of experience in data analysis and advanced statistical techniques is required. Familiarity with tools like SAS, SQL, and experience in financial modeling and analysis of large datasets are also critical for candidates aspiring to join our team.

American Express provides a comprehensive benefits package for Senior Managers, Risk Management, including competitive base salaries, bonus incentives, and a generous retirement savings plan with a 6% company match. Employees also enjoy extensive health insurance options, paid parental leave, and access to wellness centers, ensuring their holistic well-being. These benefits reflect our commitment to supporting our team members both personally and professionally.

Yes, Senior Managers, Risk Management at American Express have the flexibility to telecommute up to two days per week. We understand that work-life balance is important, and we aim to provide our employees with the opportunity to work remotely to accommodate their personal needs while still fulfilling their professional responsibilities.

Essential skills for a successful Senior Manager, Risk Management at American Express include proficiency in data analysis and statistical techniques, familiarity with machine learning algorithms, and the ability to turn complex data analyses into actionable insights. Experience with R and STATA is required, as is the skill to communicate findings to both technical and non-technical audiences. Strong partnership and collaboration capabilities are also key to thrive in this role.

When responding, consider detailing specific methodologies you've utilized in previous roles. Highlight how you've applied these techniques to real-world scenarios and how they led to improved outcomes for your past employers.

Provide a structured response by mentioning the dataset specifics, the tools you used like SQL or SAS, and the insights derived from your analysis. Emphasize the impact your findings had on the project or organization.

Discuss your engagement with industry literature, professional development courses, or conferences you attend. Mention how you apply this knowledge in your work to continuously improve strategies.

Detail a specific project where you converted unstructured data into actionable insights. Explain the methods you used and how the results benefited stakeholders.

Be honest and specify techniques you're familiar with such as regression analysis, cluster analysis, or econometrics. Offer examples of how you've applied these techniques in past projects.

Share your approach in working with cross-functional teams, focusing on communication skills, project management techniques, and how you ensure alignment of goals across departments.

Provide strategies you implement such as using visualizations, simplifying jargon, or tailoring your message to your audience's level of understanding. Point out how this has helped in making informed decisions.

Be specific about the data source you identified, how you evaluated its potential, and the results after its integration into your risk management strategies.

Discuss your focus on compliance and cultivating relationships with regulatory bodies. Mention specific examples of amendments you've made in response to feedback and their impacts.

Outline your background in financial modeling with examples of models you've created, the impact they had on your organization, and key software you’ve used, such as Excel or specialized modeling tools.