Director-Data Science (New York, NY)

The user wants me to reformat a job posting into clean, well-structured semantic HTML. Let me analyze the content and apply the rules. First, I need to identify the sections: - About The Team (appears twice - once at top, once near bottom) - How will you make an impact in this role? (this seems like an "About the role" section) - Responsibilities (with sub-sections) - Qualifications (Minimum and Preferred) - About Us (company info) - Benefits (listed in the second "About The Team" section) - Pay/Salary range mentioned at the end Rules: - Use

for section headings - Use

• for lists - Use

  for prose - Don't repeat job title as heading - Don't put Job ID/requisition numbers as headings - Preserve ALL substantive information - Remove boilerplate (EEO, legal, scam warnings, application instructions, cookie/navigation) - Include section ONLY when real specific content exists - No filler/placeholder text - No Pay/Schedule/Benefits sections unless actually stated - Output ONLY HTML fragment Let me structure this: 1. About the Team (first one) - has substantive content 2. About the Role (from "How will you make an impact...") 3. Responsibilities - with sub-sections as list items or nested? The responsibilities have key areas with descriptions. I'll make each key responsibility a list item with the title and description. 4. Qualifications - Minimum and Preferred as separate lists 5. About Us (company description) 6. Benefits - from the second "About The Team" section which lists benefits 7. Pay - there's a salary range mentioned at the end The second "About The Team" is actually benefits. The first is team description. I'll combine or separate? The first "About The Team" describes the GSDS team. The second "About The Team" describes company benefits. I'll make two sections: "About the Team" and "Benefits". Also, there's "About Us" which is company culture. Let me parse carefully. The posting starts with "Job Description Director – Data Science, Global Servicing Decision Science" - this is the title, don't repeat. Then "About The Team" - describes GSDS team. Then "How will you make an impact in this role?" - this is the role overview. Then "Responsibilities" with "Key Responsibilities" and sub-sections. Then "Qualifications" with Minimum and Preferred. Then "Depending on factors such as business unit requirements..." - visa sponsorship note. Then "About Us" - company culture. Then "About The Team" again - but this time it's benefits: "We back you with benefits that support your holistic well-being..." and lists benefits. Then "For a full list of Team Amex benefits, visit our Colleague Benefits Site." - this is a link, but we should include the benefits listed. Then EEO statement - remove. Then "We back our colleagues with the support they need to thrive..." - Amex Flex description. Then "US Job Seekers - Click to view the “Know Your Rights” poster." - remove. Then salary range statement. So sections: - About the Team (GSDS description) - About the Role (impact) - Responsibilities - Qualifications (Minimum and Preferred) - About Us (company culture) - Benefits - Pay (salary range mentioned) Visa sponsorship note - could be a small paragraph in Qualifications or separate? It's a note about visa sponsorship. I'll include as a paragraph in Qualifications or after. The rule: "fold minor metadata into a short

  or drop it." Visa sponsorship is minor metadata? It's a note about visa sponsorship. I'll include as a paragraph. Now, for Responsibilities: there are 5 key areas each with multiple bullet points. I'll make a list where each item is a key responsibility with its description. Since they have sub-bullets, I could nest lists. But the rule says use

  • for any list of duties. I'll make each key responsibility a list item, and within it, include the description and sub-points as nested list or just text. The sub-points are part of the responsibility. I'll include them as nested
    inside the
    • . Similarly for Qualifications: Minimum and Preferred each have bullet points. I'll make two separate lists under subheadings? But the rule says use

      for section headings. Minimum and Preferred could be

      ? But the rule only mentions

      for section headings. It says "use

      for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So Qualifications is a section heading. Minimum and Preferred are sub-sections. I could use

      but not specified. Safer to use

      for Qualifications and then use

      for Minimum and Preferred? The rule doesn't forbid other headings, but says use

      for section headings. I'll use

      for Qualifications and then

      for Minimum and Preferred, or just make them list items with bold labels. But the rule says use

      • for any list. I'll make two separate lists with headings. I'll do:

        Qualifications

        Minimum Qualifications

        ...

        Preferred Qualifications

        ...
        But the rule says "use

        for section headings". It doesn't say not to use other headings. I think it's fine. Alternatively, I could make Minimum and Preferred as list items with strong text. But they are distinct categories. I'll use

        . Now, for Benefits: there's a list of benefits. I'll make a

        with each benefit as
        • . Pay: "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." But no actual range given? It says "The below represents the expected salary range" but then no numbers. Probably the range was omitted in the copy. The text says "The below represents the expected salary range for this job requisition." but no numbers follow. So there's no specific pay data. The rule: "never create Pay/Schedule/Benefits sections unless the posting actually states them." Since no actual range is stated, I should not create a Pay section. The statement is generic. I'll omit Pay section. Similarly, Schedule: not mentioned. Now, remove boilerplate: EEO, legal, scam warnings, application instructions, "US Job Seekers...", "Know Your Rights", etc. Also remove "For a full list of Team Amex benefits, visit our Colleague Benefits Site." - that's a link, but we have the benefits listed. I'll keep the listed benefits. Now, write HTML. Let me draft. First section: About the Team (GSDS)

          About the Team

          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.

          Second: About the Role

          About the Role

          As Director, you will define and lead the vision, strategy, and execution of Decision Science across Global Servicing, translating complex customer and business challenges into scalable intelligence capabilities that improve customer experience, colleague effectiveness, operational efficiency, membership value, and controls. This is a highly visible leadership role requiring deep analytical rigor, strong technical and AI expertise, strategic problem-solving, commercial acumen, and enterprise leadership. You will lead a high-performing team of data science professionals and partner across Global Servicing and the enterprise to embed intelligent decisioning into servicing experiences and processes. You will also help shape the next generation of servicing Decision Science—advancing capabilities such as Agentic AI, transformer-based recommendation systems, and Conversational AI while ensuring solutions are production-ready, measurable, governed, and continuously improving.

          Third: Responsibilities

          Responsibilities

          • GSDS Strategy & Business Impact: Define and lead the Decision Science roadmap across Global Servicing, identifying and prioritizing high-impact opportunities across servicing experiences, membership value and engagement, colleague efficiency, and operational excellence. Translate business strategy into clear Decision Science priorities, success measures, and investment choices, connecting technical opportunities to measurable customer and business outcomes.
          • AI / GenAI & Decision Science Leadership: Provide technical leadership across AI/ML, GenAI, prediction, recommendation, optimization, experimentation, and learning, setting a high bar for solution design, evaluation, and analytical rigor. Drive the evolution of GSDS toward emerging AI paradigms, including Agentic AI and multi-agent workflows, transformer-based recommenders and representation learning, and Conversational AI/LLM-based systems that can reason over context and support increasingly intelligent servicing decisions. Maintain sufficient technical depth to challenge architectures, modeling choices, evaluation frameworks, and trade-offs, and to guide teams from experimentation through scalable production deployment.
          • Scalable Decisioning Products & Production AI: Oversee development of reusable, production-ready data science products and decisioning systems that leverage customer, behavioral, contextual, and operational data to enable timely and personalized decisions. Partner with Technology, platform, and governance teams to deploy and evolve AI solutions with appropriate architecture, observability, controls, model/AI quality, and lifecycle discipline.
          • Leadership, Talent & Enterprise Influence: Lead, mentor, and grow a high-performing team of data science professionals, fostering technical excellence, first-principles problem solving, innovation, ownership, and strong commercial judgment. Build organizational capability across Applied GenAI, AI engineering and architecture, advanced recommendation and decisioning methods, strategic problem solving, and commercial storytelling. Influence senior stakeholders and build strong cross-functional accountability, using clear and compelling narratives to drive prioritization, investment decisions, adoption, and execution of major Decision Science initiatives.
          • Innovation & Future-Focused Capability Building: Continuously evaluate advances in AI and Decision Science and translate the most relevant methods into practical, scalable capabilities and reusable best practices for Global Servicing. Shape a forward-looking technical roadmap that strengthens GSDS capabilities in Agentic AI, Conversational AI, modern recommendation systems, experimentation, AI engineering, architecture, governance, and continuous optimization.
          Fourth: Qualifications

          Qualifications

          Minimum Qualifications

          • Bachelor's degree in a quantitative field (e.g., Engineering, Computer Science, Mathematics, Statistics, Economics).
          • Exceptional analytical and conceptual problem-solving ability, with experience structuring and solving complex, ambiguous business challenges using first-principles thinking.
          • Proven leadership experience managing and developing high-performing analytics or data science teams in a complex, cross-functional environment.
          • Strong technical foundation in modern data science and AI, with the ability to guide solution design, challenge technical approaches, and connect analytical choices to business outcomes.
          • Strong ability to influence senior stakeholders through clear, structured, and compelling communication and executive storytelling.