Payments Data Scientist I

Worldpay•Cincinnati, OH

3d•$91,900 - $138,700

About The Position

Ready to take your career global? Turn complex data into insights and intelligent products that make everyday commerce better. As a Data Scientist at Global Payments, you’ll apply machine learning, statistical modeling and strong engineering skills to solve meaningful business and client challenges. You’ll join a connected team where you can learn from experienced data scientists, contribute your ideas and build your expertise. You’ll have the opportunity to work with large, complex datasets while shaping practical solutions that balance analytical accuracy, performance and business value. In this role, you’ll transform data into clear insights and scalable solutions that strengthen decisions, enhance data-driven products and create better outcomes for our clients. You’ll own your work, influence technical approaches and build the knowledge you need to help shape the future of commerce.

Requirements

A bachelor’s degree in Statistics, Decision Sciences, Applied Mathematics, Economics, Computer Science or an equivalent combination of education, training and experience.
Demonstrated engineering and mathematical capabilities, typically gained through at least two years of experience in software analytics or a related field.
Knowledge of machine learning, artificial intelligence, statistical modeling, data visualization and data analysis.
Proficiency with relevant data science tools and programming languages, such as Python, R, Scala and SQL.
Experience with or knowledge of cloud-based technology, solutions design and requirements analysis.
Strong analytical, decision-making and problem-solving skills, with the judgment to turn complex challenges into practical solutions.
Clear written and verbal communication skills, a collaborative mindset and the confidence to influence the best approach across technical and nontechnical groups.

Nice To Haves

Knowledge of financial services will strengthen your ability to make an impact.

Responsibilities

Transform complex data into meaningful insights that guide decisions, uncover opportunities and create value for internal teams, partners and clients.
Build and enhance data-driven products using machine learning, artificial intelligence and statistical modeling to improve business and client outcomes.
Shape large and complex datasets into reliable, usable formats that enable accurate analysis and scalable solutions.
Apply the right technical approach using tools and programming languages such as Python, R, Scala and Structured Query Language (SQL).
Influence analytical system design by translating requirements into thoughtful recommendations and contributing to project planning with experienced data scientists and cross-functional teams.
Create clear, compelling analyses that make complex findings understandable and actionable for technical and nontechnical audiences.
Protect model quality and performance by documenting your work, writing maintainable code and monitoring models and products against defined outcomes.
Make pragmatic, business-aware decisions by balancing sophistication and accuracy with implementation effort, performance and cost.