Manager - Data Science

You Lead the Way. We've Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you'll learn and grow as we help you create a career journey that's unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you'll be recognized for your contributions, leadership, and impact-every colleague has the opportunity to share in the company's success. Together, we'll win as a team, striving to uphold our company values and powerful backing promise to provide the world's best customer experience every day. And we'll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

Our industry is rapidly evolving, and we need courageous, quick thinkers who can shape the strategic decisions that lead our business forward. Whether it's negotiating with some of our largest global partners or creating next year's financial plan, you can influence both our day-to-day P&L and the future direction of the company. As part of the team, you can have the opportunity to learn and use the latest data tools and technologies and explore a range of roles to grow your career. Find your place in finance on #TeamAmex.

Finance Data Science & Analytics team's focus is to build predictive models grounded in data and leverage Machine Learning techniques to add stability and predictability to the AXP P&L. FDS team's goal is to help the organization make fact-based and scientifically developed decisions around risk and opportunities.

Responsibilities:

• Lead the design, planning, and execution of machine learning projects, ensuring alignment with the company's strategic goals and objectives.
• Innovate with a focus on developing newer and better revenue models using big data and machine learning solutions.
• Design, develop, and deploy machine learning models to predict spending and lending patterns, delivering value to finance colleagues and business partners.
• Leverage causal inference framework to determine drivers and their contribution in revenue growth
• Utilize advanced data analysis and visualization techniques to explain model outputs and extract insights that support decision-making processes.
• Collaborate with key stakeholders, including senior management, partners, and the model validation group, to drive the success of machine learning projects.
• Lead model documentation efforts and partner with the model validation team to ensure compliance with regulatory guidelines.

Minimum Qualifications:

• Minimum of 3+ years of experience in data science or machine learning, with a focus on developing and deploying machine learning models.
• BS/MS or PhD in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Chemistry, Operations Research, etc.) with hands-on experience leveraging sophisticated analytical and machine learning techniques.
• Expertise in an analytical language (Python, R, or the equivalent), and experience with databases (Hive, SQL, or the equivalent) is required.
• Demonstrated ability to frame business problems into mathematical programming problems, leverage external thinking and tools (from academia and/or other industries) to engineer a solution and deliver business insights.
• Ability to work effectively in a team environment.
• Independent thinker who is organized, has great attention to detail, and can multi-task.
• Strong communication skills, Ability to integrate with cross-functional business partners worldwide.
• Ability to learn quickly and work independently with sophisticated, unstructured initiatives.

Preferred Qualifications:

• Experience with data visualization is a plus.
• Machine Learning Knowledge: Deep understanding of machine learning/statistical algorithms such as deep learning, boosting, and causal inference.

Considerations for sponsorship:

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws,

American Express may provide visa sponsorship for certain positions

Qualifications

Salary Range: $90,000.00 to $165,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

• Competitive base salaries
• Bonus incentives
• 6% Company Match on retirement savings plan
• Free financial coaching and financial well-being support
• Comprehensive medical, dental, vision, life insurance, and disability benefits
• Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
• 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
• Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
• Free and confidential counseling support through our Healthy Minds program
• Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

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