\\\\Description\\\\ 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 this 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. \\\\How will you make an impact in this role?\\\\ Global Commercial Services (GCS) is the global leader in providing payments solutions for Small, Medium, and Large Enterprises. We are in the business of helping our clients get business done! Accelerating sales and driving profitable charge volume growth are critical for the success of the organization. The Sales Enablement team is instrumental in driving these objectives. The Senior Manager will play a critical role supporting the development of growth and data-driven strategies to improve Sales portfolio performance and drive execution, while working alongside senior leadership within GCS. The ideal candidate should demonstrate creativity, curiosity, and passion for dealing with large amounts of data and converting it into valuable, actionable information. We seek a thought-leader and a problem-solver who can blend business, technical, and industry best practices when it comes to developing data-driven solutions. The position will provide consultative support to the GCS Sales leadership team through development of analytical solutions. The incumbent will highlight trends, risks, and opportunities to enhance business decision-making processes, while working very closely with Sales, Marketing, Finance, Technology, and Capabilities partners to drive Sales growth. The incumbent will lead a team of data scientists to design, develop, and test ML/AI-derived solutions that deliver higher client engagement and efficiency improvements. The role is positioned at a unique intersection of deepening analytics and informing business outcomes. This is a fast-paced environment requiring a mix of strong relationship skills, passion for applied data science, people leadership, and a singular focus on excellence. \\\\Key Responsibilities:\\\\ \\+ Lead Data Science Projects: Design, develop, and deploy predictive and explanatory analytical solutions that address critical business problems using machine learning, NLP, and generative AI. Strengthen forecasting, refine incentive plan designs, and identify gaming behaviors \\+ Drive Analytics: Deliver high-impact analytics to inform strategy by developing actionable insights into Sales and client behavior. Introduce new approaches to transform complex behavioral data and influence decision-making across the organization \\+ GenAI Analytics Use Case Development: Lead key workstreams in the design, development, and operationalization of a GenAI-enabled analytics solution that synthesizes internal performance and external competitive signals into actionable insights, with defined success metrics and ongoing monitoring \\+ Develop Modeling Capabilities: Build and evaluate models using modern ML frameworks (e.g., TensorFlow, PyTorch), focusing on scalability, performance, and interpretability \\+ People Leadership: Lead a team of high-performing data scientists \\+ Collaborate Across Teams: Establish and maintain close relationships with key cross-functional stakeholders to understand business strategies, develop goals, and address opportunities \\+ Develop Scalable Solutions: Architect and deploy robust, efficient, and scalable data pipelines and modeling solutions using modern cloud and distributed compute patterns \\+ Lead Innovation Through External Perspective: Stay current on advancements in machine learning, deep learning, and generative AI; evaluate emerging approaches; translate theoretical advances into practical, scalable solutions that advance business outcomes. Challenge the status quo and demonstrate strong curiosity \\+ Define Performance Indicators: Lead analytics and measurement across key performance indicators. Own stakeholder and executive-level communications on initiative progress, including automated monthly measurement tied to specific strategic initiatives \\+ Communicate Insights Effectively: Present findings, recommendations, and results to both technical and non-technical audiences, including executive leadership, through clear reports, visualizations, and presentations, to enable data-driven decision-making \\\\Minimum Qualifications:\\\\ \\+ 4-5 years of relevant work experience \\+ Bachelors degree required, preferably in a quantitative field (e.g., Economics, Finance, Computer Science, Mathematics/ Statistics, Engineering) \\+ Strong analytical and conceptual thinking acumen, with ability to translate complex, unstructured business problems into quantitative models. Leverage external insights and tools (from academia or other industries) where needed \\+ Capable of articulating key findings to senior leadership and stakeholders, leveraging insights to influence business decisions \\+ Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and experience applying algorithms to real-world business problems \\+ High proficiency in Python/SQL is required; experience with Hadoop and Spark is a plus \\+ Experience with data querying and distributed analytics tools (e.g., Hive, PySpark, BigQuery) is required \\+ Experience in a Big Data environment, including data mining and data processing. Ability to address performance issues and to manipulate both structured and unstructured data \\+ Demonstrable experience with data visualization and reporting tools (e.g., matplotlib, seaborn, Tableau) \\+ Proficiency with industry-recognized ETL methods, processes and standards \\+ Advanced knowledge of Microsoft Office Suite (Excel pivot tables, deck-writing) \\+ Ability to work independently as well as collaboratively in a dynamic, cross-functional environment, with a strong attention to detail and passion for learning \\\\Preferred Qualifications:\\\\ \\+ Masters/PhD in a quantitative field (Computer Science, Statistics, Econometrics, Mathematics, Physics, Operation Research, Engineering, etc.) \\+ 2 years experience of applying machine learning techniques to real-world business problems, including exposure to production ML and/or GenAI (e.g., LLM prompting, RAG, evaluation) \\+ Stakeholder management at the executive level \\+ People leadership experience \\\\Qualifications\\\\ Salary Range: $123,000.00 to $215,250.00 annually bonus benefits The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, well consider your location, experience, and other job-related factors. 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. 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, 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: \\\\Job:\\\\ Marketing \\\\Primary Location:\\\\ US-New York-New York \\\\Schedule\\\\ Full-time \\\\Req ID:\\\\ 26003645

A Bachelor's degree in a quantitative field such as Economics, Finance, Computer Science, Mathematics/Statistics, or Engineering is required. The role necessitates 4-5 years of relevant work experience. Strong analytical and conceptual thinking are essential for translating complex business problems into quantitative models. Proficiency in Python and SQL is mandatory, with experience in data querying and distributed analytics tools like Hive, PySpark, and BigQuery being required. Familiarity with machine learning libraries and frameworks such as TensorFlow, PyTorch, and scikit-learn is also required, along with demonstrable experience in data visualization and reporting tools. A Master's or PhD in a quantitative field and 2 years of experience applying machine learning techniques, including exposure to production ML and/or GenAI, are preferred qualifications.