Visa is a world leader in payments technology, facilitating transactions globally. They are seeking an Associate Data Scientist to support data science efforts, contribute to analytics and AI-powered solutions, and collaborate with various teams to drive data-driven decision making.
Contribute to the development and deployment of analytics and machine learning models, supporting use cases from data exploration through validation and implementation under guidance from senior team members
Apply Generative AI techniques (e.g., prompt engineering, LLM-based text analysis, summarization, and classification) to enhance data analysis, insight generation, and internal workflows
Leverage largescale datasets using tools such as SQL, Python, R, or Hive, combining traditional statistical methods with ML and GenAI-assisted approaches to uncover trends and actionable insights
Use AI-powered development tools (e.g., coding assistants, AutoML, and notebook automation) to accelerate experimentation, improve code quality, and increase productivity
Build and maintain BI dashboards and reports, and support user adoption through documentation, walkthroughs, and guidance on best practices for BI usage
Develop intuitive visualizations and dashboards to communicate insights and model outputs to technical and non-technical audiences
Support model deployment and monitoring efforts, collaborating with data engineering teams and following established MLOps, data governance, and responsible AI guidelines
Partner with product, marketing, operations, and finance teams to understand business questions and translate them into analytical tasks
Assist in framing business problems into analytical approaches, contributing to data-driven solutions that inform product and operational decisions
Present insights and recommendations using structured storytelling, clearly explaining assumptions, limitations, and potential business impact
Support prioritization of analytics initiatives by considering business value, data availability, and technical feasibility in collaboration with senior team members
Communicate technical findings in simple, actionable terms to nontechnical partners and stakeholders
Help drive adoption of analytics solutions by validating results, documenting methodologies, and demonstrating how insights address real business needs
Collaborate closely with cross-functional teams to iterate on analyses and improve solutions based on feedback
Qualification
Required
Bachelor's or Master's degree in Computer Science, Computer Engineering, CIS/MIS, Cybersecurity, Statistics, Business or a related field, graduating May 2025 - August 2026
Preferred
2+ years of experience in data analysis, quantitative modeling, or data driven decision making in an academic or professional setting
Proficiency in SQL and Python for data analysis and modeling
Experience extracting, transforming, aggregating, and analyzing large datasets using SQL, Python, R, and Spark, including exploratory data analysis and feature engineering
Hands on experience using Generative AI or AI-assisted tools (e.g., LLMs, coding assistants, AutoML) to support data analysis, insight generation, or workflow efficiency
Applied experience with Generative AI techniques, such as prompt engineering, text summarization, classification, or LLM assisted analysis, through coursework, projects, or professional work
Familiarity with responsible AI considerations, including data privacy, bias awareness, and model limitations
Solid foundation in statistics and machine learning, including regression, classification, and model evaluation techniques
Hands on experience building descriptive and predictive models using machine learning libraries and tools such as scikit learn, Jupyter notebooks, Python, R, and/or SAS
Exposure to data mining and statistical modeling techniques, including regression, clustering, decision trees, and related methods
Experience in building and maintaining BI solutions using tools like Tableau, Power BI, or similar platforms, including metrics definitions, semantic layers, data quality validation, and user support
Effective communication and collaboration skills, with the ability to explain data driven insights clearly to business stakeholders and translate analysis into actionable recommendations for technical and non-technical audiences
Experience organizing and managing analytical work using productivity tools such as Excel, Word, PowerPoint, and collaboration platforms (e.g., Teams)
Exposure to financial services, payments, credit cards, or merchant analytics is a plus but not required
Benefits
Medical
Dental
Vision
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness Program
Visa is a multinational financial services company that facilitates electronic payment systems throughout the world.
