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Manager - Data Science - job 11 of 13

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

At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way.

When you join Team Amex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day. Here, you’ll learn and grow as we champion your meaningful career journey with programs, benefits, and flexibility to back you personally and professionally. Every colleague shares in the company’s success.

Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to our customers, communities, and each other every day. And, we’ll do it with integrity and in an environment where everyone is seen, heard and feels like they truly belong.

Join #TeamAmex 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.

How will you make an impact in this role?

The Finance Data Science & Analytics team drives strategic decisions for the business by applying statistical, innovative, analytical approaches and machine learning techniques. The candidate will be part of a quantitative finance team made up of highly talented individuals with strong intellectual curiosity. The essence of the work involves gathering, manipulating and synthesizing data (customer behaviors, transactions, attributes, etc.), predictive modeling and analytics to drive actionable recommendations. This is an excellent opportunity for an individual to work with the leadership team, gain deeper understanding of AXP business and build key business relationships. 

Candidate will support the analytics and forecasting for US Card Services Lending business, and work closely with broader Finance community, Business and Risk teams to drive profitable growth for the company.

Responsibilities include:

  • Leverage quantitative skills to provide decision support to business teams on key initiatives
  • Assist in developing/enhancing lend metric predictive modeling that incorporates card member behaviors and increased level of data granularity
  • Use machine learning techniques to improve forecasts and produce business insights; leverage visualization and reporting tools
  • Understand and adopt emerging technology that can affect the application of the quantitative analytical approaches and technique to solve business problems
  • Partner across Finance, Risk and Business to derive strategic insights and evaluate profitability
  • Ensure the flow of accurate and complete financial information by liaising between internal and external reporting and broader finance organization.
  • Provide thought leadership into key findings and actionable recommendations to influence business strategy
  • Perform corporate planning and financial planning and analysis that serve as the basis for key internal and external communications.
  • Develop product profitability analytics to support investment and strategic decisions
  • Help maintain documentation for monthly CFO management reporting, quarterly results, business events, and accounting changes. Support internal and external reporting by performing year-over-year financial analysis.

Ensure integrity of financial information for internal and external stakeholders. Identify financial control gaps and opportunities for efficiencies and create enhancements.

Minimum Qualifications

    • Bachelor’s / Master’s degree in a quantitative field
    • 2+ years of experience preferred
    • Proficiency in Python, SQL or Hive
    • Python/R skills strongly preferred
    • Statistical/Predictive modeling knowledge and experience strongly preferred
    • Highly motivated individual with desire to work on ambiguous projects; With the ability to break down and execute on complex ideas
    • Strong analytical, organizational, and problem-solving skills with good attention to detail
    • Ability to solve ad hoc business problems independently and manage multiple priorities and projects while adhering to deadlines
    • Strong desire and ability to learn

    Please note, Salary increases in case of a lateral move are provided only on an exception basis and in line with compensation guidelines.

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. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including, but not limited to, the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.

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.

US Job Seekers - Click to view the “Know Your Rights” poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster

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

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Average salary estimate

$127500 / YEARLY (est.)
min
max
$90000K
$165000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Manager - Data Science, American Express

Join the innovative team at American Express as a Manager - Data Science in New York, New York, where you'll help shape the future of finance through data-driven decision-making. At American Express, we believe in empowering our team members to lead the way, ensuring that we all support each other in achieving our professional and personal goals. In this exciting role, you will harness your quantitative skills to provide insights that drive the business forward. You'll work with a talented group of analysts to analyze customer behaviors, develop predictive models, and utilize cutting-edge machine learning techniques to enhance our business strategies. You’ll collaborate with various departments, including Finance, Business, and Risk, to provide actionable recommendations and ensure the integrity of financial reporting. This is not just a job; it's an opportunity to impact our company's direction. We value curiosity and encourage a culture of continuous learning. You'll have the chance to gain firsthand experience with advanced data tools and technologies while fostering key relationships within the company. As part of Team Amex, you'll enjoy excellent benefits, a competitive salary range, and the flexibility to create a work-life balance that suits your needs. Together, we can redefine what’s possible. So bring your ambition, creativity, and analytical skills to American Express, and let’s lead the way together in making finance a more dynamic and impactful industry.

Frequently Asked Questions (FAQs) for Manager - Data Science Role at American Express
What are the primary responsibilities of a Manager - Data Science at American Express?

As a Manager - Data Science at American Express, your primary responsibilities include leveraging quantitative skills to support business decisions, developing predictive modeling for lend metrics, utilizing machine learning techniques to improve forecasts, and collaborating across Finance, Risk, and Business to derive strategic insights. You'll also ensure the flow of accurate financial information while providing thought leadership on actionable recommendations that influence business strategy.

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What qualifications are needed for the Manager - Data Science position at American Express?

To qualify for the Manager - Data Science position at American Express, candidates should possess a Bachelor’s or Master’s degree in a quantitative field, along with at least 2 years of relevant experience. Proficiency in Python, SQL, or Hive is essential, along with strong knowledge of predictive modeling and statistical techniques. Strong analytical, problem-solving skills, and a desire to learn in a fast-paced environment are also highly valued.

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How does American Express support career growth for Data Science Managers?

American Express actively supports career growth for Data Science Managers through various programs and benefits. You’ll have opportunities for professional development, including access to training resources and career advancement programs. By working with a diverse group of talented individuals, you can also explore different roles within the organization, allowing you to expand your skill set and drive your career forward.

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What tools and technologies will I use as a Manager - Data Science at American Express?

In the Manager - Data Science role at American Express, you'll use a variety of advanced tools and technologies to analyze data effectively. This includes proficient use of programming languages like Python and R, along with SQL for database management. You'll also have the opportunity to work with visualization tools to deliver insights and forecasts, as well as leverage emerging technologies that can enhance your analytical approach to business challenges.

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What is the work environment like for a Manager - Data Science at American Express?

The work environment for a Manager - Data Science at American Express is dynamic and collaborative. You will work with cross-departmental teams in a culture that values inclusivity and promotes open communication. The company also offers flexible work arrangements, allowing you to choose between hybrid, onsite, or fully remote work, depending on your role and business needs.

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Common Interview Questions for Manager - Data Science
How do you approach predictive modeling in your data analysis?

When approaching predictive modeling, it's crucial to understand the business problem at hand. I start by gathering relevant data and then dissect it to identify patterns or trends. Next, I choose the right algorithms based on the problem's requirements, focusing on accuracy and relevance. Finally, I validate models using test datasets and iterate upon them to ensure they provide actionable insights.

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What experience do you have with machine learning techniques?

I have hands-on experience implementing various machine learning techniques like regression analysis, decision trees, and cluster analysis. I focus on selecting the right models that suit the specific data and business objectives. Additionally, I have used machine learning to enhance forecasting and drive efficiencies, leading teams in exploring new methods for data handling and analysis.

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Can you give an example of a challenging data problem you've solved?

A challenging data problem I encountered involved accurately predicting customer churn. By thoroughly analyzing behavioral data and customer feedback, I employed a combination of logistic regression and decision trees that allowed us to identify significant churn indicators. Implementing this model enabled our team to proactively engage at-risk customers, thus reducing churn rates significantly.

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How do you ensure data quality and accuracy in your analyses?

To ensure data quality and accuracy, I implement a comprehensive data validation process. This includes reviewing data sources, creating automated checks for anomalies, and maintaining clear documentation on data handling processes. Regular audits and updates on data collection methodologies also help uphold the integrity of the data used in analyses.

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What is your experience working in cross-functional teams?

I have substantial experience working in cross-functional teams, which I consider vital in driving successful projects. Collaboration with departments such as Finance, Risk, and Business helps me understand their unique perspectives and challenges. By aligning our goals and leveraging diverse expertise, we can create inclusive strategies that benefit the company as a whole.

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How do you prioritize projects and tasks in your role?

Prioritizing projects involves assessing urgency, impact on business goals, and resource availability. I typically use a project management tool to list tasks, define deadlines, and assign responsibilities. Regularly liaising with stakeholders ensures that I'm aligned with the organization's shifting priorities and strategic objectives.

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What tools do you prefer for data visualization and reporting?

I prefer using tools like Tableau and Power BI for data visualization as they allow for intuitive visual storytelling. These tools enable me to communicate complex data findings in a clear and impactful manner. I also value Excel for ad hoc reporting due to its versatility and accessibility, making it suitable for quick analyses.

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How do you keep up with industry trends in data science?

I stay updated with industry trends by regularly participating in webinars, following data science thought leaders on platforms like LinkedIn, and engaging in professional communities. Furthermore, I prioritize continuous learning through online courses and certifications that enhance my expertise in emerging tools and methodologies.

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What is your approach to stakeholder communication in data projects?

Effective communication with stakeholders is essential for successful data projects. I begin by clearly defining project goals and expectations and maintain open lines of communication throughout the project lifespan. Regular updates, presentations of findings, and adapting communication styles to suit the audience help build trust and ensure stakeholder engagement.

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How do you manage changing requirements during a data project?

Managing changing requirements requires flexibility and strong change management practices. I ensure that the project scope includes a process for assessing and integrating changes. Open communication with stakeholders allows me to understand their evolving needs and adjust objectives without compromising project integrity and timelines.

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American Express is a multinational financial services corporation and global leader in providing personal, small business, and corporate credit cards.

3018 jobs
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BADGES
Badge Family FriendlyBadge Office VibesBadge Work&Life BalanceBadge Rapid Growth
CULTURE VALUES
Inclusive & Diverse
Empathetic
Collaboration over Competition
Growth & Learning
Transparent & Candid
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Mental Health Resources
Life insurance
Disability Insurance
Child Care stipend
Employee Resource Groups
Learning & Development
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
April 19, 2025

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