Senior Data Science Analyst

Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant services.  Our worldwide team helps over 3 million companies, more than 1,300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results.  We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions.  Join our dynamic team and make your mark on the payments technology landscape of tomorrow.  Summary of This Role Deploys data-driven exploratory analysis as well as predictive models to solve business problems across financial services industry, particularly in the area of Originations, Risk and Fraud, Digital engagement, Payments and Customer Management. Designs and analyzes experiments to test new product ideas and convert the results into actionable product recommendations. Leads Analytics Model development, validation and maintenance. Assists with data collection, cleaning, visualization, model building, training, testing, and presentations to build analytics capability and drive efficiencies in business areas across TSYS.  What you’ll own    Design and build statistical/ML models (regression, classification, and related techniques) to replace manual analysis and surface predictive insight. Engineer features and validate models with discipline — testing robustness, assessing performance, and choosing methods that fit the business problem. Rebuild report and analytical logic as SQL transformations in cloud data warehouses (e.g., Snowflake/BigQuery/Redshift/Synapse), working comfortably across large, unfamiliar schemas Validate parity vs. legacy outputs; reconcile discrepancies and document assumptions Translate model outputs into business-readable insights, visuals, and clear recommendations for stakeholders. Use AI tools to speed analysis and drafting while maintaining accuracy and controls  What you’ll bring   Must-Have   BS in Statistical Background, Computer Science, Information Technology, Business/Management Information Systems, or related field 5-8 years  of relevant experience, typically Python : hands-on proficiency with pandas, scikit-learn, and statsmodels for data preparation, modeling, and analysis SQL : proficient working with large datasets; able to write complex queries and move comfortably across unfamiliar schemas; Snowflake experience is a plus Statistical modeling : strong foundation in regression, classification, and hypothesis testing; able to choose methods that fit the business problem Feature engineering and model validation : able to create useful predictors, test model robustness, and assess performance with discipline Data visualization : able to translate model outputs into business-readable insights, visuals, and clear recommendations Comfort with fragmented, incomplete data : able to navigate multiple disconnected source systems, reconcile inconsistencies, and piece together a coherent picture without hand-holding AI-first mindset : daily user of AI tools (Copilot/ChatGPT/Claude or similar) to speed analysis and drafting; already works this way (not "will learn") Attention to detail : finance-grade accuracy; output feeds executive and regulatory reporting It’s a bonus if you have          Background on Credit Risk , Lending   Snowflake or any cloud data warehouse (BigQuery, Redshift)  Experience in financial services, payments, or fintech  Python or basic scripting  Cross-domain data analysis: exposure to working with data from more than one business function or system; comfortable joining datasets that weren’t designed to be joined This is a good opportunity to bring in some of our values and behaviors:   Think like a client: We care deeply about our clients' success. We ask, listen and learn — curious to understand first. Our passion drives excellence in everything we