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, 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.

Job Description

The IDS team is looking for a manager to lead, design, and implement high‑impact analytics, machine learning, and Generative AI solutions. This role combines technical leadership, hands-on data engineering, traditional statistical modeling, and cutting-edge AI development, including LLMs and agentic workflows.

The ideal candidate is a versatile data scientist and engineer who can work from raw data all the way to production-grade solutions, building models, developing automation pipelines, and leveraging Generative AI to transform how VCA delivers insights to clients in Latin America.

Responsibilities:

• Drive (hands-on) the end‑to‑end lifecycle of analytical, machine learning, and Generative AI projects—from business problem definition to model development, validation, deployment, and monitoring.
• Perform (hands-on) advanced data wrangling, feature engineering, and dataset creation using complex, large‑scale, and unstructured data sources (Hadoop, PySpark, Presto, SQL, Hive).
• Build and deploy traditional ML and statistical models (Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, K-Means Clustering, LLM, XGBoost, Neural Networks, …).
• Develop and implement Generative AI solutions, including LLM‑based pipelines, retrieval‑augmented generation (RAG), prompt engineering, and AI agents for automation and decision support.
• Collaborate with engineering teams to design scalable solutions that integrate both ML and GenAI components into production environments.
• Create frameworks and reusable components to accelerate internal model development and improve team efficiency.
• Translate complex analytical concepts into actionable recommendations for technical and non‑technical stakeholders.
• Mentor junior data scientists, fostering excellence in analytical methods, coding best practices, and emerging AI techniques.
• Promote the adoption of Generative AI across the organization, identifying opportunities for automation, knowledge enhancement, and operational efficiency.
• Build strong client relationships, supporting scoping discussions, requirement gathering, roadmap development, and solution delivery.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 

Qualifications

Basic Qualifications:

• 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Preferred Qualifications:

• 7+ years of relevant work experience in developing machine learning models with a Bachelor's degree, OR 4+ years with an Advanced Degree (Master or PhD).
• Post-graduate degree in a quantitative field such as Statistics, Mathematics, Data Science, Computer Science, Informatics, Economics, or Engineering (Master or PhD).
• Minimum of 5+ years of hands-on expertise in applying and deploying Machine Learning solutions to solve business problems, with proven experience in the complete model lifecycle (development, validation, and production deployment).
• Deep theoretical and practical knowledge of machine learning techniques, including but not limited to Linear/Logistic Regression, Decision Trees (Random Forests, XGBoost), Clustering, and Neural Network.
• Strong programming proficiency in Python and its data science ecosystem (e.g., Pandas, Scikit-learn, NumPy, PySpark) for building and implementing ML models.
• Proven ability to perform data manipulation and feature engineering on large, complex datasets using distributed computing platforms (e.g., Hadoop, PySpark) and database systems (SQL, Hive, Python).
• Experience in presenting complex analytical results and ideas to stakeholders and tailoring communication to various audience levels.
• Hands on experience with Generative AI, including LLMs, fine tuning, prompt engineering, RAG, and creation of AI agents.
• Experience leading or mentoring technical teams.
• Deep understanding of the Payments and Banking industry.
• Experience with data visualization tools such as Tableau.
• Familiarity with MLOps frameworks and cloud computing environments.
• Fluency in English and Spanish (spoken/written). Portuguese language skills are 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.