Data Science Associate, Intelligence & Data Solutions (IDS)

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients. VCA's core client segments include issuers, acquirers, merchants, fintechs, payment enablers and governments.

The Intelligence & Data Solutions (IDS) team at VCA consists of data scientists, analysts, and engineers who provide analytics solutions. Their goal is to leverage VisaNet, one of the largest datasets globally, to help clients enhance their performance and increase profitability.

Key Responsibilities:

• Assist in the execution of analytic projects along with the rest of the stakeholders both internal and external.
• Collaborate with different teams to provide desired business outcomes.
• Assist in defining detailed analytic scope and methodology and create an analytic plan.
• Support the analytic plan with appropriate data mining and analytic techniques.
• Perform QA on data and deliverables to ensure consistency and accuracy.
• Ensure all project documentation is up to date and all projects are reviewed per analytic plan.
• Support project delivery within timelines and budget requirements.
• Support existing analytic techniques by promoting new methodology and best practices in the analytic field.

This is a hybrid position. Employees in hybrid roles are expected to work from the office 3 set days a week (Tuesday - Thursday), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic Qualifications:

• Permanent authorization to work in Singapore
• Has less than 12 months of relevant data scientist experience
• Hands-on experience in developing machine learning models, scaling data solutions and delivering end-to-end data science projects
• Proficiency in statistical techniques such as Regression, Decision Trees, Random Forests, Neural Networks, etc.
• Knowledge in data mining and modeling techniques like Predictive Modeling, Classification, and Decision Trees.
• Competence in Excel and BI Tools such as PowerPoint or Tableau.
• Experience with statistical software - Python, SAS, R, Stata, etc. extract and aggregate data using SQL or similar tools.
• Previous exposure to financial services or credit card analytics is a plus.
• Strong business acumen and problem-solving skills using data-driven methods.
• Team-oriented, collaborative, and flexible with the ability to tailor results to different audiences.
• Attention to detail to ensure quality in reports and data analysis.
• Ability to translate analytics into actionable recommendations.
• Experience in presenting ideas and analysis to stakeholders.
• Exhibit intellectual curiosity and a desire to continually learn.

Preferred Qualifications:

• Experience in developing and applying Generative AI and Agentic AI solutions
• Experience in geospatial data analysis

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.