Senior Managers, Risk Management - job 28 of 32

As a Senior Manager in Risk Management at American Express, you'll design and implement comprehensive business strategies and risk management solutions, analyzing both structured and unstructured data. You'll collaborate with technology teams to integrate risk management policies, evaluate new data sources for profitability, and ensure that our methodologies follow industry best practices while fulfilling regulatory requirements.

To apply for the Senior Manager, Risk Management position at American Express, you will need a Master’s degree in a relevant field such as Finance, Mathematics, or Statistics, along with at least one year of experience in data analysis. Skills in advanced statistical techniques and familiarity with tools like SAS, SQL, and R are also required.

The salary range for a Senior Manager, Risk Management at American Express is between $128,211 and $165,000 annually. Factors such as experience and location will ultimately influence your compensation.

Yes, American Express offers flexibility with telecommuting options for the Senior Manager, Risk Management role, allowing up to 2 days of remote work per week.

As a Senior Manager in Risk Management at American Express, you can expect competitive base salaries, bonus incentives, a 6% company match on retirement savings, comprehensive healthcare benefits, and generous paid parental leave, among other wellness and career development programs.

When responding, focus on specific projects where you've applied statistical modeling techniques. Discuss the types of analyses you performed, the tools you utilized (like SAS or R), and how your findings impacted the business decisions.

Share your approach to transforming unstructured data into actionable insights. Mention the tools and techniques you use, such as data mining and analysis, and provide examples of how this has led to improved risk management strategies.

Explain how you conduct initial assessments of data sources, including collecting relevant metrics and running hypothesis tests. Provide examples from your past work that demonstrate your analytical thought process and results.

Illustrate this with a specific experience where you simplified complex data insights. Highlight your ability to use visuals and plain language to convey meaningful information to stakeholders without a technical background.

Discuss your strategies for working with cross-functional teams. Emphasize how important communication and cooperation are to integrating risk management policies effectively.

Mention resources like industry publications, online courses, and professional networks. Discuss how you apply your learnings into your work processes to enhance risk management methodologies.

Describe your practical experience in financial modeling, including specific techniques you've used. Provide tangible examples of how your models have impacted business financial decisions.

Discuss specific machine learning algorithms you've implemented, how they apply to risk management, and the outcomes achieved. Emphasize your problem-solving skills in real-world applications.

Explain your method for assessing and prioritizing risks based on their potential impact and likelihood. Provide an example that illustrates a successful decision-making scenario.

Highlight the tools you're most proficient in, such as SAS, SQL, or R, and explain why you prefer them based on their features and your success with those tools in previous roles.