Payments Data Scientist I: AI-Driven Insights

Global Payments Inc.; Cincinnati (OH); On-site; USD 92,000 - 139,000; Full time

Job summary

Global Payments Inc. is seeking a Data Scientist I to apply analytics and AI/ML techniques to solve business problems and support data-driven decision making.

You will collaborate with cross-functional teams to develop insights, build predictive models, and deliver solutions that improve operational and business performance. The role emphasizes transforming complex data into meaningful insights, designing data-driven products, and communicating findings to diverse audiences with a pragmatic,

Qualifications

• Bachelor's or master's degree in a quantitative field.
• Experience with data analysis, ML, and predictive modeling.
• Proficiency in Python, R and SQL; comfortable with large datasets.

Responsibilities

• Transform complex data into actionable insights for decision-making.
• Build, validate and improve data-driven products using ML and statistical modelling.
• Develop data visualizations, dashboards, and reports for technical and non-technical audiences.
• Collaborate with cross-functional teams to translate business needs into analytical solutions.
• Ensure data quality and reliable data formats across large datasets.
• Support deployment and monitoring of analytical models and data products.

Skills

Data analysis

Machine learning

Statistical modeling

Data visualization

Cross-functional collaboration

Problem solving

Education

Bachelor's or Master's in Data Science/Statistics/Math/CS/Engineering/Economics

Tools

Python

R

SQL

Cloud platforms

Job description

Global Payments Inc. is seeking a Data Scientist I to apply analytics and AI/ML techniques to solve business problems and support data-driven decision making.

You will collaborate with cross-functional teams to develop insights, build predictive models, and deliver solutions that improve operational and business performance. The role emphasizes transforming complex data into meaningful insights, designing data-driven products, and communicating findings to diverse audiences with a pragmatic,