Senior Data Science Analyst

Global Payments · Pune

  • Experience5–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted17 Sept 2026

About Global Payments

Global Payments is hiring in Pune in financial services. This role looks for around 5+ years of experience.

Skills

  • Python
  • pandas
  • scikit-learn
  • statsmodels
  • SQL
  • statistical modeling
  • regression
  • classification
  • hypothesis testing
  • feature engineering
  • model validation
  • data visualization
  • machine learning

The role

A data scientist at a payments and financial services company designs statistical modeling and machine learning solutions for credit risk, fraud, payments, and customer management, using Python and SQL. The role translates predictive insights into experiments, visualizations, and product recommendations while validating models and working across cloud data warehouses.

Full job description

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 set out to do.

Act like an owner: We take accountability — working at pace to own our outcomes. We empower each other to make decisions. We’re innovative — always finding better ways to deliver impact.

Win as one team: We value personal connections — moving forward together with clarity. We build inclusive and global teams — embracing different perspectives and ideas. It’s always ‘we,’ never ‘me.’ We’re determined to succeed together.

About the team

Our inclusive and global teams win together every day. We’re proud to have the best minds in the industry, who you can learn from as you grow your career. The people, the energy, the connections – it’s unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that go beyond borders.

What makes a Globalpayer?

Globalpayers think like a client, act like an owner and win as one team. We’re curious and innovative – always finding better ways to deliver impact. We empower each other to make decisions, and it’s our passion that drives excellence in everything we set out to do.

Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.

Global Payments Inc. is an equal opportunity employer. Global Payments provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex (including pregnancy), national origin, ancestry, age, marital status, sexual orientation, gender identity or expression, disability, veteran status, genetic information or any other basis protected by law. If you wish to request reasonable accommodations related to applying for employment or provide feedback about the accessibility of this website, please contact jobs@globalpayments.com.