Analyst-Data Science (SQL, ML&GENAI)
American Express · Posted Oct 5
Banking, credit card, payment network, and travel services
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About the role
The Analytics, Investments and Marketing Enablement (AIM) team within Global Commercial Services Marketing (GCSM) powers customer acquisition, engagement, and retention through data, advanced analytics, and AI. Within AIM, the Customer Experience Optimization (CXO) Personalization – GCS Digital Acquisitions team builds scalable, intelligent personalization for SME customers across acquisition channels, sitting at the intersection of AI/GenAI, advanced analytics, and digital product. This role executes personalization strategies and develops analytical solutions that improve customer engagement and conversion, working with cross-functional partners to embed personalization into digital experiences using SQL, machine learning, and GenAI.
What you will do
- Assist in executing personalization strategies across digital touchpoints (e.g., website, landing pages, application flows).
- Analyze customer behavior and contextual data to support targeted messaging, content, and offers.
- Work with product and engineering teams to help implement personalization features on digital platforms.
- Support development of personalization use cases using basic machine learning or GenAI techniques (e.g., segmentation, next-best-action).
- Help with data preparation, model inputs, and testing under guidance.
- Contribute to experimentation and evaluation of AI-driven features.
- Work with structured and unstructured data to generate insights.
- Build queries, dashboards, and basic analytical models.
- Contribute to reusable code and analysis pipelines with guidance.
- Assist in monitoring model performance and reporting key metrics.
- Break down business problems into smaller analytical tasks with support.
- Generate insights from data and present findings clearly.
- Support measurement and analysis of personalization initiatives.
Skills used in this role
What the employer is looking for
- Master’s degree in a quantitative discipline such as Engineering, Mathematics, Computer Science, Physics, Finance, or Economics.
- 1+ years of experience in data science, advanced analytics, machine learning, decision science, or related quantitative roles.
- Strong programming skills in Python and SQL, with hands-on experience developing machine learning models and analytical solutions.
- Strong communication and interpersonal skills, with the ability to deliver clear insights and collaborate across teams.
Preferred qualifications
- Experience developing AI/ML, NLP, or Generative AI/LLM-based solutions.
- Experience building scalable analytical workflows and production-ready solutions.
- Prior experience in marketing analytics, commercial analytics, personalisation or digital data.
- Familiarity with web/app analytics tools or experimentation platforms.
Benefits and support
- Competitive base salaries
- Bonus incentives
- Support for financial-well-being and retirement
- Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- Generous paid parental leave policies (depending on your location)
- 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
About American Express
American Express Company is a globally recognized multinational financial services corporation specializing in payment cards, travel-related services, and network banking. Founded in 1850, the company provides charge and credit cards, expense management products, and merchant services to consumers, small businesses, and large corporations worldwide. It operates a proprietary payments network known for its premium customer engagement and lifestyle rewards programs.
- Industry
- Banking
- Company size
- 76800 employees
- Founded
- 1850-03-18
- Location
- New York City, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Information Officer and Executive Vice President
Chief Colleague Experience Officer
Chief Marketing Officer
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