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Manager - Data Science - job 8 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

If you’re ready to step into a role that blends leadership and innovation, the Manager - Data Science position at American Express in New York is calling your name! Here, we believe in empowering our team members with the right backing to thrive. As part of Team Amex, you’ll be joining a diverse community focused on delivering exceptional experiences each and every day. Your role will be pivotal in shaping the strategic decisions that drive our business forward, engaging deeply with our Finance Data Science & Analytics team. You’ll leverage your quantitative skills to lead initiatives that support our US Card Services Lending business, collaborating with brilliant minds to build predictive models, analyze customer behaviors, and employ machine learning techniques to generate actionable insights. This is no ordinary data job; it's an opportunity to work closely with leadership, forge impactful business relationships, and play a vital role in helping us achieve profitable growth. We’re seeking someone who isn’t just skilled in Python and SQL but also showcases a strong analytical mindset, as your findings will directly influence our business strategies. If you're excited about data-driven decision-making and looking to work in an environment where your contributions are valued, American Express is the place to be. Come join us and lead the way in a role where your potential is celebrated and your growth supported!

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

As a Manager - Data Science at American Express, your responsibilities include providing decision support for key business initiatives, leveraging quantitative skills to drive actionable insights. You will develop predictive modeling incorporating card member behaviors, use machine learning techniques to enhance forecasts, and partner with different teams within Finance and Risk to derive strategic insights, ensuring the accuracy and integrity of financial information.

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

To qualify for the Data Science Manager position at American Express, candidates should have a Bachelor’s or Master’s degree in a quantitative field, along with 2+ years of experience in a similar role. Proficiency in Python, SQL, and statistical modeling is essential, alongside strong analytical and problem-solving skills. Candidates must demonstrate a passion for data and a readiness to tackle complex projects independently.

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How does American Express support professional growth for a Data Science Manager?

American Express places a high value on professional development for its employees, including those in the Data Science Manager role. The company offers various training opportunities, career development resources, and programs designed to foster meaningful career growth. You will have the chance to work with the latest tools in data science and collaborate with high-level leadership, gaining valuable insights into the business.

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

In the Data Science Manager role at American Express, you will work with advanced data tools and technologies, including Python and SQL for data manipulation, machine learning techniques for modeling, and various visualization and reporting tools to present your analytical findings effectively. Familiarity with Hive may also be beneficial, as you work to synthesize customer behavior data into actionable business insights.

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

The work culture for a Data Science Manager at American Express is dynamic and inclusive. The company emphasizes collaboration, innovation, and integrity, encouraging every colleague to share their voice and contribute to team success. You'll find an environment that supports flexibility, creativity, and a commitment to empowering one another, fostering a sense of belonging for all its team members.

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Common Interview Questions for Manager - Data Science
Can you describe your experience with quantitative data analysis?

When answering this question, highlight specific projects where you've utilized quantitative analysis, detailing the methodologies used, the data tools applied, and the outcomes achieved. Demonstrating how your analytical skills informed business decisions will showcase your fit for the Manager - Data Science role.

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What statistical modeling techniques are you familiar with?

In your response, emphasize your knowledge of various statistical modeling techniques, such as regression analysis, time-series forecasting, or classification models. Providing examples of how you’ve applied these techniques in previous roles can help illustrate your practical experience in analytics.

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How do you prioritize projects when working on multiple initiatives?

Explain your approach to project prioritization, mentioning any frameworks or tools you use to assess project impact, deadlines, and resource availability. Demonstrating your ability to handle multiple priorities while maintaining quality will be key for a Manager - Data Science at American Express.

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Describe a challenging analytical problem you faced and how you resolved it.

Share a relevant experience where you encountered a significant analytical challenge. Discuss the steps you took to resolve it, focusing on your problem-solving skills and the impact of your solution on the business outcome. This showcases your ability to tackle complex scenarios effectively.

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What is your experience with machine learning, and how have you implemented it in your work?

Highlight your familiarity with machine learning techniques and algorithms you’ve implemented in past projects. Share specific applications or use cases that demonstrate how you utilized machine learning to add value and drive business insights.

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How do you ensure data integrity when working on financial models?

Discuss the methods you use to check data quality, including validation processes, reconciliation techniques, and thorough documentation practices. This will show your commitment to maintaining high standards of accuracy, which is crucial for a Data Science Manager role.

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How do you adapt to new technologies in the data science field?

Illustrate how you keep yourself updated on the latest technologies and trends in data science through continuous learning, attending seminars, or participating in professional groups. This shows your adaptability to change, which is crucial in a fast-evolving industry.

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Describe your experience working cross-functionally with other teams.

Provide examples of past collaborations with other departments, emphasizing how you communicated your findings effectively to non-technical stakeholders. Highlighting your teamwork and ability to articulate complex data concepts will showcase your fit for an interdepartmental role.

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What tools and platforms do you prefer for data visualization, and why?

Explain your preferred data visualization tools (e.g., Tableau, Power BI, Matplotlib) and the rationale behind your choice. Discuss how these tools helped communicate insights effectively to your audience, demonstrating your ability to present complex information clearly.

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How do you motivate your team to achieve project goals?

Share your leadership style and how you inspire and guide a team to meet objectives. Mention specific strategies you employ to create a motivated and cohesive team environment, which is particularly relevant in a managerial position at American Express.

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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 20, 2025

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