Manager-Data Science (New York, NY)

Reposted Yesterday
New York, NY, USA
Hybrid
Entry level
Fintech • Financial Services
The Role
Develops and owns end-to-end decision science initiatives, including predictive modeling, recommendation, optimization, experimentation, and GenAI solutions. The role applies agentic AI, transformer-based recommenders, conversational AI, and LLMs to servicing use cases. Responsibilities include building production-ready data science products, partnering with technology and business teams, measuring impact, optimizing models, leading workstreams, and communicating recommendations to stakeholders.
Summary Generated by Built In

The Global Servicing Decision Science (GSDS) team is the Decision Science engine for Global Servicing, bringing together advanced analytics, data science, AI/GenAI, and decisioning to transform servicing experiences, empower colleagues, and enable intelligent operations. GSDS serves as a centralized Decision Science Center of Excellence, partnering across Product/Capabilities, Control Management, Strategy, Operations, Technology, and enterprise analytics and data science teams.

GSDS builds and scales servicing intelligence across Global Servicing—from predictive and proactive servicing, personalization, next-best-action and journey orchestration to conversational AI, agent assist, AI-powered coaching, conduct and quality monitoring, and complaint and dispute intelligence. Our mandate is to build durable, production-ready capabilities that continuously improve decisions through prediction, recommendation, optimization, experimentation, and learning.

As a Manager, you will contribute to and increasingly own end-to-end Decision Science work that helps build the next generation of servicing intelligence at American Express. You will translate customer, colleague, and operational challenges into analytical approaches, models, experiments, and scalable AI-driven solutions, working with business and Technology partners to move capabilities from concept through implementation and optimization.

This role combines hands-on technical depth with strong business problem solving. You will work on modern capabilities—including Agentic AI, transformer-based recommendation systems, and Conversational AI—while building your ability to lead workstreams, influence partners, and connect technical solutions to measurable customer and business outcomes.

Responsibilities

Decision Science and Business Problem Solving: 

  • Own defined Decision Science problems and workstreams—from problem framing and analysis through solution development, experimentation, measurement, and ongoing optimization—with guidance only on the most complex or ambiguous challenges.

  • Develop analytical approaches and decisioning solutions across servicing experiences, personalization and membership value, colleague enablement, and operational excellence.

AI/GENAI & Advanced Modeling 

  • Design and develop AI/ML and GenAI solutions spanning prediction, recommendation, optimization, experimentation, and intelligent orchestration.

  • Apply and evaluate modern AI approaches—including Agentic AI and agentic workflows, transformer-based recommenders and representation learning, Conversational AI/LLM systems, and advanced personalization or next-best-action methods—to servicing use cases.

  • Make sound modeling and evaluation choices, identify data requirements and solution trade-offs, and seek technical guidance where needed to ensure analytical rigor and practical scalability.


Scalable Solutions & Execution: 

  • Build and enhance reusable data science products and decisioning capabilities, working with Technology and platform teams to support productionization and measure impact.

  • Apply robust experimentation, monitoring, and continuous-learning approaches that improve model/AI quality and business outcomes over time.


Leadership & Cross Functional Influence: 

  • Lead defined workstreams and contribute to the development of other colleagues through collaboration, knowledge sharing, and technical support, while demonstrating strong ownership and problem solving.

  • Synthesize analysis into clear recommendations and narratives; communicate effectively with partners and contribute to decisions on solution choices, priorities, and execution.

Qualifications
  • Bachelor’s degree in quantitative fields (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics, Finance).

  • Strong analytical and conceptual problem-solving skills, with the ability to structure and solve business problems and work through ambiguity.

  • Strong hands-on foundation in data science and machine learning, with proficiency in Python, SQL, or similar tools and experience building and evaluating predictive or decisioning models.

  • Experience applying AI/GenAI techniques, with a strong technical foundation in solution development, experimentation, and model/AI evaluation.

  • Experience owning analytical workstreams and collaborating across cross-functional teams to move solutions from analysis and development toward implementation and measurable impact.

  • Strong written and verbal communication skills, with the ability to translate technical work into clear business recommendations and collaborate effectively with stakeholders.

Preferred Qualifications: 

  • Experience with Agentic AI/agentic workflows, transformer architectures or transformer-based recommendation systems, Conversational AI, LLMs, or related modern AI capabilities.

  • Experience with personalization, recommendation systems, next-best-action, optimization, customer decisioning, or intelligent automation.

  • Understanding of the end-to-end Decision Science lifecycle, including experimentation, productionization, monitoring, governance, and continuous optimization.

  • Experience working with large-scale customer, behavioral, interaction, or operational datasets and developing reusable data science products.

  • Developing commercial acumen and storytelling skills, with the ability to connect analytical and technical choices to customer and business value.

 

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.

About Us

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

About the Team

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

  • 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 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.


The below 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.​

Skills Required

  • Bachelor's degree in a quantitative field such as engineering, computer science, mathematics, statistics, economics, or finance.
  • Strong analytical and conceptual problem-solving skills, including the ability to structure and solve ambiguous business problems.
  • Hands-on foundation in data science and machine learning.
  • Proficiency in Python, SQL, or similar tools.
  • Experience building and evaluating predictive or decisioning models.
  • Experience applying AI or Generative AI techniques.
  • Technical foundation in solution development, experimentation, and model or AI evaluation.
  • Experience owning analytical workstreams and collaborating cross-functionally to implement solutions and deliver measurable impact.
  • Strong written and verbal communication skills, including translating technical work into business recommendations.
  • Experience with agentic AI, agentic workflows, transformer architectures, transformer-based recommendation systems, conversational AI, LLMs, or related modern AI capabilities.
  • Experience with personalization, recommendation systems, next-best-action, optimization, customer decisioning, or intelligent automation.
  • Understanding of the end-to-end decision science lifecycle, including experimentation, productionization, monitoring, governance, and continuous optimization.
  • Experience working with large-scale customer, behavioral, interaction, or operational datasets and developing reusable data science products.
  • Commercial acumen and storytelling skills connecting analytical and technical choices to customer and business value.

American Express Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about American Express and has not been reviewed or approved by American Express.

  • Healthcare Strength — Health coverage and wellness resources are broad, combining comprehensive medical, dental, and vision with mental-health support and virtual care. These offerings are cited as a core strength of the overall package.
  • Parental & Family Support — Paid parental leave for all parents, backup childcare, eldercare support, and adoption or fertility assistance create a family-forward package. These resources are viewed as generous and practical for caregivers.
  • Retirement Support — A competitive 401(k) match alongside options like profit sharing, stock bonuses, and pension or retirement savings plans strengthens long-term security. Retirement programs are positioned as a meaningful complement to base pay.

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The Company
HQ: New York, NY
100,703 Employees
Year Founded: 1850

What We Do

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 striving to uphold our powerful backing promise to our customers and each other every day. These beliefs have been our North Star for 170 years as our business transformed – from helping evacuate travelers during World Wars, to ensuring the safety of our customers’ funds during the Great Depression in the U.S., to creating the Shop Small® movement to help small businesses recover from the Financial Crisis, to providing aid to communities impacted by many natural disasters and so much more. For generations, the key to our success has been the determination and resilience of our American Express colleagues. Now, as a globally integrated payments company, we work together to provide customers with access to products, insights and world-class experiences that enrich lives and build business success. Join us and let’s lead the way together.

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