As an Analyst - Risk Management, you will contribute to the development and deployment of predictive models designed to enhance AML efforts across American Express's products and services. You will work with large data sets, implement machine learning algorithms, and create innovative solutions to tackle financial crime risk. This is an exciting opportunity to collaborate with teams across the organization to help drive data-driven decision-making and further the company’s commitment to fighting financial crime.
Responsibilities
- Develop, deploy, and validate predictive models designed for AML use cases.
- Implement machine learning algorithms (e.g., Gradient Boosting, Isolation Forest) to automate and enhance decision-making processes.
- Leverage GenAI and other emerging technologies to build and optimize solutions for risk management.
- Analyze large, complex data sets to derive actionable business insights and create innovative data science solutions.
- Use supervised and unsupervised techniques to improve the effectiveness of transaction monitoring and risk detection.
- Work closely with teams such as Global Financial Crimes Compliance (GFCC), Financial Intelligence Unit (FIU), and CFR to understand business needs and provide actionable solutions.
- Present findings to leadership and key stakeholders, translating technical insights into business value.
- Set up and monitor the performance of models using internal tracking and smart monitoring tools.
- Ensure models are performing at optimal levels and making intelligent, relevant decisions based on transaction data.
- Continuously explore innovative approaches and techniques using big data and machine learning to enhance AML mitigation strategies.
- Stay informed of industry developments in finance, payments, and analytics to apply external insights into internal solutions.
- Drive end-to-end data science solutions and ensure they meet business requirements.
- Collaborate with internal governance teams to ensure compliance and secure approvals for new model implementations.
Minimum Qualifications
- Bachelor's Degree in Economics, Statistics, Computer Science, or a related field.
- 2-4 years of experience in analytics or big data workstreams, with at least 2 years of experience in Risk Management or Financial Crimes Analytics.
- Proficiency in Python (including data science libraries such as Pandas, NumPy, scikit-learn) and SQL.
- Strong understanding of mathematics and statistics, with the ability to apply these principles to data science and modeling.
- Experience with model deployment and working in developer environments (e.g., version control using Git).
- Ability to drive projects to completion and work effectively within a collaborative team environment.
- Strong communication skills, with the ability to clearly present technical findings to both technical and non-technical stakeholders.
- Ability to work independently with complex, unstructured data and initiatives.
Preferred Qualifications
- Expertise in coding algorithms, high-performance computing, and scalable solutions.
- A good understanding of AML investigations, payment industry regulations, and decision science frameworks.
- Experience with GenAI or other emerging technologies.
- Familiarity with cloud technologies and distributed computing.
- Strong problem-solving skills and ability to innovate in challenging situations.
Benefits
- Competitive base salaries and bonus incentives.
- Medical, dental, vision, life insurance, and disability benefits (depending on location).
- Flexible working model with hybrid, onsite, or virtual arrangements based on role and business needs.
- Generous paid parental leave policies (depending on location).
- Access to on-site wellness centers, with free and confidential counseling support.
- Career development and training opportunities.
Why American Express?
At American Express, we are committed to a culture of inclusion, innovation, and integrity. We empower our employees to make a meaningful impact, grow their careers, and take advantage of a wide range of benefits and programs that support their well-being at every stage of life.
How to Apply. Click the Apply button to submit your application. Ensure your resume highlights your experience in data science, machine learning, and financial crime risk management.