Finance Data Science Intern - Predictive Analytics (Summer)

Egug; New York (NY); On-site; USD 55,000 - 69,000; Full time

Job summary

American Express in New York offers a Finance Data Science & Analytics internship focused on building and applying modeling capabilities to real business problems. You’ll work with large datasets, develop predictive models, and translate questions into technical modeling approaches while communicating insights clearly to stakeholders.

You will gain hands-on experience with SQL, Python, and ML techniques, contributing to forecasting, risk assessment, and strategic decision-making across Finance,

Qualifications

• Currently enrolled in a full-time graduate degree program in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Quantitative Finance, AI, Physics, or related field.
• Expected graduation date between Dec 2027 and Jun 2028.
• 3+ years of prior relevant full-time work experience.
• Experience with predictive modeling, machine learning, statistical analysis, optimization, or applied data science.
• Ability to translate business questions into technical modeling approaches and communicate results.

Responsibilities

• Develop predictive models and analytical frameworks to forecast key metrics.
• Apply ML and statistical methods to identify drivers of business performance.
• Build, validate, and interpret models to inform decisions on growth, profitability, risk, and balance sheet management.
• Translate business problems into analytical questions and measurable outcomes.
• Collaborate with Finance, Business, Risk, and Technology teams to embed model-driven insights.

Skills

Analytical thinking

Communication

Problem solving

Education

Graduate degree program in Data Science/Statistics/CS

Tools

SQL

Python

R

Power BI

Job description

American Express in New York offers a Finance Data Science & Analytics internship focused on building and applying modeling capabilities to real business problems. You’ll work with large datasets, develop predictive models, and translate questions into technical modeling approaches while communicating insights clearly to stakeholders.

You will gain hands-on experience with SQL, Python, and ML techniques, contributing to forecasting, risk assessment, and strategic decision-making across Finance,