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Manager-Data Science (New York, NY)

Egug Open
Hybrid New York Full-time Manager Data Science

At a glance

Manager-level Data Science role at Egug. New York · full-time · no salary stated · we estimate $137,825–$205,600.

Estimated pay

Egug has not published a salary for this role. The figure below is our estimate, not theirs.

$137,825 – $205,600
What the middle half of mid-level data science roles in New York paid, among postings that did state a salary.
Worked out from 61 postings that stated pay, median $155,000. Last updated Nov 13, 2026.
RoleData Science
SeniorityManager
LocationNew York
WorkplaceHybrid
EmploymentFull-time
PostedNov 12, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Take defined servicing decision-science problems from framing and analysis through model development, testing, measurement and refinement
  • Build AI and machine-learning approaches for prediction, recommendations, optimization and intelligent orchestration in servicing
  • Assess newer methods such as agentic workflows, transformer recommenders and conversational AI for servicing applications
  • Work with technology and platform teams to put reusable data-science capabilities into production and track their impact
  • Lead workstreams, share technical knowledge with colleagues and turn analysis into clear recommendations for partners

What you bring

  • A bachelor’s degree in a quantitative discipline such as engineering, computer science or mathematics
  • Hands-on data-science and machine-learning experience, including Python, SQL or similar tools and building and assessing models
  • Experience applying AI or generative AI, developing solutions and evaluating their performance
  • Experience owning analytical work and working across teams to move solutions toward implementation and measurable results

Who this fits

This manager-level role suits someone who combines practical modeling skills with business problem solving and can lead defined workstreams while developing their influence with partners. The position is hybrid in New York City. Visa sponsorship may be available depending on the role and business circumstances.

From the employer

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.

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.

  • 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.

Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Science

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.