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Senior Analyst - Data Science - job 1 of 4

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 2+ 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.

Salary Range: $55,000.00 to $105,000.00 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/Employees - Click here to view the “Know Your Rights” poster and the Pay Transparency Policy Statement.

If the links do not work, please copy and paste the following URLs in a new browser window: https://www.dol.gov/agencies/ofccp/posters to access the three posters.

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Average salary estimate

$80000 / YEARLY (est.)
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$55000K
$105000K

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 Senior Analyst - Data Science, American Express

As a Senior Analyst - Data Science at American Express in New York, New York, you'll be at the forefront of our innovative finance data science and analytics team. Here, you’ll lead exciting machine learning projects that directly influence our business strategy and P&L. We believe in backing our team members to help them achieve their full potential. With the right support, you'll have the opportunity to design and deploy predictive models that drive revenue growth. Collaborating with a diverse group of stakeholders and utilizing advanced data analysis techniques, you'll unlock valuable insights that shape our decision-making processes. In this role, you’ll deepen your expertise in analytical languages like Python or R while working with sophisticated databases and machine learning algorithms. You'll also contribute to our mission by innovating new revenue models, enhancing our understanding of spending and lending patterns, and ensuring our projects align with regulatory compliance. At American Express, we understand the value of a cohesive work environment where each team member feels heard and appreciated. You'll have the chance to grow your skills while making a significant impact on our strategies. Join us, and let’s lead the way together with your analytical prowess and passion for data science!

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

The Senior Analyst - Data Science at American Express is responsible for leading the design and execution of machine learning projects. This role involves innovating on revenue models, deploying predictive models, collaborating with senior management, and ensuring compliance with regulatory guidelines. Additionally, the analyst uses advanced data analysis to extract valuable business insights.

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What qualifications do I need to apply for the Senior Analyst - Data Science position at American Express?

Candidates for the Senior Analyst - Data Science position must have a minimum of 2 years of experience in data science or machine learning. A BS, MS, or PhD in a quantitative field is required. Proficiency in analytical languages like Python or R and experience with databases such as Hive or SQL are also essential qualifications.

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How does American Express support career growth for a Senior Analyst - Data Science?

At American Express, career growth is a priority. As a Senior Analyst - Data Science, you will have access to various training and development opportunities. You'll work with the latest data tools and technologies and collaborate with different teams, enabling you to expand your skill set and advance your career within the company.

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What kind of projects would I work on as a Senior Analyst - Data Science at American Express?

In the role of Senior Analyst - Data Science at American Express, you would work on innovative machine learning projects designed to understand consumer behavior. This includes developing predictive models for spending and lending, enhancing revenue strategies, and utilizing causal inference techniques to determine key drivers for revenue growth.

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

The work environment for the Senior Analyst - Data Science at American Express is vibrant and collaborative. Emphasis is placed on inclusivity and support, ensuring that every colleague feels valued and can thrive. You will be part of a diverse team that fosters innovation and personal development while achieving shared successes.

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Common Interview Questions for Senior Analyst - Data Science
Can you describe your experience with machine learning algorithms as a Senior Analyst - Data Science?

When discussing your experience with machine learning algorithms, focus on specific projects you have worked on. Explain the algorithms you used, such as deep learning or boosting, and how they contributed to a successful outcome. Emphasize your ability to select the right algorithm for different types of data and problems.

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How do you approach problem-solving in data science?

In data science, problem-solving begins with understanding the business context. Discuss your method of framing business problems into mathematical terms. Highlight how you utilize data analysis and statistical techniques to derive solutions, and give examples of successful projects driven by your problem-solving approach.

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What tools and technologies have you utilized in your data science projects?

Be specific about the tools and technologies you've used, such as Python, R, SQL, Hive, or data visualization tools. Discuss how you leveraged these tools to address project challenges effectively. Providing examples of achieved results using these tools can strengthen your response.

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How do you ensure compliance with regulatory guidelines in your projects?

Compliance is critical in data science, especially in finance. Explain your experience in creating model documentation and collaborating with model validation teams. Emphasize your understanding of regulatory requirements and your proactive steps in ensuring your projects remain compliant.

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Describe a challenging data science project you worked on.

When discussing a challenging project, outline the problem, your approach, and the outcomes. Focus on the methods you used and how you navigated obstacles. Sharing metrics that illustrate the success of your project demonstrates your effectiveness as a Senior Analyst in Data Science.

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How do you stay current with advancements in data science and machine learning?

Staying current in data science involves continuous learning. Discuss any courses, certifications, or conferences you participate in. Mention specific industry-relevant publications or blogs you follow, and emphasize how you apply new knowledge or trends to your work.

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Can you give an example of a time you collaborated with cross-functional teams?

Collaboration is key in data science. Share an experience where you worked with non-technical partners, focusing on your communication strategy and how you ensured mutual understanding. Highlight the outcomes achieved through this collaborative effort.

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What is your experience with data visualization?

Discuss your familiarity with data visualization tools and techniques. Provide examples of how you’ve presented complex data insights to stakeholders using visual aids. Highlight how effective visualization can influence decisions and help stakeholders understand key takeaways.

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How do you handle ambiguous data or unstructured initiatives?

Handling ambiguity requires strong analytical skills. Describe your approach to breaking down unstructured data into manageable components. Emphasize your willingness to explore and iterate on solutions, showcasing your ability to adapt to evolving project requirements.

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Describe how you prioritize tasks in a multi-project environment.

Prioritization in a multi-project environment is crucial. Discuss your method for assessing deadlines, business impact, and dependencies. Highlight any tools or techniques you use to stay organized, ensuring that you can effectively manage your time and responsibilities across several projects.

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

2281 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 4, 2025

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