Manager, Visa Consulting and Analytics (VCA), Intelligence & Data Solutions at Visa

São Paulo, São Paulo, Brazil -

Full Time

Start Date

Immediate

Expiry Date

23 Jun, 26

Salary

0.0

Posted On

25 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, AI/ML Models, Hadoop Ecosystem, PySpark, SAS, Presto, SQL, Data Wrangling, Machine Learning Algorithms, Data Mining, Consulting Solutions, Predictive Modeling, Statistical Modeling, Project Management, Relationship Management, Presentation Skills

Industry

IT Services and IT Consulting

Description

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. Team 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, fintech's, 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. Job Description Lead, develop, and strengthen high‑impact stakeholder relationships across internal teams and Visa clients. Build and deploy advanced analytical and AI/ML models across Visa and VCA clients (issuers, acquirers, merchants), following AI‑First principles. Work with large‑scale, complex datasets, extracting, cleansing, transforming, and manipulating data using tools such as Hadoop ecosystem, PySpark, SAS, Presto, SQL, and related technologies. Oversee robust data‑wrangling processes, ensuring high‑quality datasets suited for predictive modeling and analytical insights. Develop, evaluate, and validate advanced data mining techniques, machine learning algorithms, and automated analytical capabilities to solve strategic business challenges. Leverage Visa’s data, AI infrastructure, and analytic assets to design, standardize, and implement scalable consulting solutions. Identify relevant market and industry trends, generating insights that inform strategic decisions in the payments ecosystem. Engage and influence internal and external stakeholders to shape analysis scope, methodologies, and solution direction. Continuously propose innovative ideas that improve analytical strategies, operational efficiency, and client value—promoting an AI‑First and experimentation culture. Conduct client‑specific analyses using proprietary portfolio data, including demographics, behavioral patterns, spend, fraud, credit risk, and financial performance. Communicate complex analytical concepts and model results clearly and effectively to executive and non‑technical audiences. Support technical knowledge transfer and ensure smooth implementation of delivered solutions. Document analytical processes, methodologies, and best practices, contributing to continuous improvement across the organization. This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. Qualifications BA or BS required, master’s degree preferred (e.g., Statistics, Computer Science, Engineering, Data Science, or related fields). 6+ years of professional experience, with at least 4 years in the Banking or Payments industry preferred. Strong interest and curiosity about the future of payments and emerging trends in the ecosystem. Experience in retail banking, payments, financial services, and/or technology industries. Demonstrated experience in Credit Risk or Fraud Prevention, including the development of policies, ad‑hoc analyses, and predictive models. Proven hands‑on expertise in advanced analytics and statistical modeling, including Linear and Logistic Regression, Clustering methods (e.g., K‑means), and Classification techniques (e.g., Decision Trees, Random Forest). Experience working with large‑scale datasets (Big Data), with strong skills in extracting, cleaning, and manipulating data using tools such as Python or PySpark, SQL, Hadoop or Hive, Presto, SAS, or similar technologies. Familiarity with data visualization tools such as Tableau or Power BI. Ability to generate and present innovative, data‑driven ideas to enhance current business practices, particularly within Risk disciplines. Excellent project management, organizational, and presentation skills. Strong teamwork, relationship management, and interpersonal skills. Ability to manage multiple projects simultaneously while meeting deadlines. Fluency in English (spoken and written), Spanish is a plus. 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. Job Family Group: Product Development

Responsibilities

The role involves leading the development and deployment of advanced analytical and AI/ML models for Visa and VCA clients, requiring work with large-scale, complex datasets using various big data tools. Responsibilities also include engaging stakeholders, identifying market trends, and communicating complex analytical results to executive audiences.