VCA team is looking for an individual to join our data science practice and play a role developing high impact projects for Visa’s clients. This potential candidate will be responsible for developing and implementing statistical modeling to address key strategic needs for Visa’s clients including issuers, acquirers and merchants.

This role will develop data driven solutions that sit atop vast Visa datasets. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data, identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations / decisions through activities like building ML models, perform jobs in big data cluster by using different execution engines and program languages such as Python, (Py)Spark, etc.

Responsibilities:

• Lead the Artificial Intelligence and Advanced Analytics strategy for consulting engagements, with a strong focus on Credit and Authorization initiatives, ensuring AI and Machine Learning models are directly tied to measurable business outcomes for issuers, acquirers, and merchants.
• Design, develop, and scale end‑to‑end AI‑driven solutions, covering the full analytics lifecycle — data exploration, feature engineering, advanced modeling, validation, deployment, continuous monitoring, governance, and model evolution in production.
• Serve as a technical and strategic authority in Data Science and AI, guiding cross‑functional teams on best practices in Machine Learning, Generative AI, MLOps, Responsible AI, explainability, and model risk management, particularly within regulated environments such as credit and payments.
• Lead advanced Credit and Authorization analytics projects, including scorecards, real‑time decisioning, approval rate optimization, loss prevention, risk management, fraud mitigation, and profitability optimization, leveraging large‑scale transactional data.
• Transform billions of transactional records into analytical products and intelligent solutions, using modern Big Data architecture, distributed processing, and scalable data pipelines (e.g., Spark, Hadoop, SQL, Python).
• Drive an AI‑First culture across the organization, promoting model reuse, standardized analytical frameworks, accelerated time‑to‑value, and enterprise‑level industrialization of data solutions.
• Translate analytical insights into strategic decisions, clearly communicating complex model outputs into actionable recommendations for executives, internal stakeholders, and clients.
• Act as a strategic partner to clients, co‑creating AI‑based solutions to address critical business challenges such as growth, profitability, credit risk, authorizations, fraud, personalization, and customer experience.
• Ensure excellence in data governance, ethics, and security, maintain regulatory compliance, responsible AI usage, and protection of sensitive data.
• Develop and lead high‑performing teams, fostering technical excellence, mentoring talent, enabling knowledge sharing, ensuring effective resource allocation, and driving agile execution of complex analytics initiatives.
• Oversee the development and deployment of analytical models and techniques for internal teams and clients, ensuring high‑quality code, thorough documentation, effective knowledge transfer, and successful implementation of solutions.
• Identify market trends and strategic opportunities through deep analysis of the payments and credit ecosystem, collaborating with internal and external stakeholders to shape analytical initiatives.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Education and Experience:

• 9 or more years of relevant professional experience with a Bachelors degree, 7 or more years with an Advanced Degree such as a Masters or MBA, or 3 or more years with a PhD in Data Science, Statistics, Computer Science, Engineering, Economics, or related fields.
• 5 or more years of experience in financial services, banking, credit cards, payments, or merchant and retailer analytics, with demonstrated exposure to credit risk, authorizations, or transaction level decisioning.
• Proven experience as a key contributor or leader in strategic, high impact analytics initiatives.

Advanced Analytics, AI and Engineering:

• Hands on experience extracting, processing, and analyzing large scale Big Data datasets using tools such as Hadoop Hive, Spark, Python, SQL, and related ecosystems.
• Strong background in advanced analytics and statistical modeling, including linear regression, logistic regression, clustering techniques such as K means, classification models, and other predictive approaches.
• Demonstrated experience developing, training, testing, and validating Machine Learning models such as Random Forest, Gradient Boosting, and SVM using Python and other ML and AI frameworks. Experience with Spark MLlib is a plus.
• Proven experience designing, deploying, and monitoring end to end Machine Learning pipelines, with deep knowledge of model performance metrics, drift detection, monitoring, and ML best practices.
• Experience building and deploying production grade, data driven applications, real time or near real time decisioning systems, and scalable data processing pipelines.

Credit, Risk and Authorization Domain Expertise:

• Strong understanding of credit risk analytics, scorecards, authorization strategies, approval optimization, loss prevention, fraud mitigation, and profitability modeling.
• Experience working with transaction level and portfolio level data, including customer demographics, spending behavior, activity patterns, and financial attributes.
• Familiarity with regulated environments, model governance, explainability, and responsible AI practices, particularly in credit and payments contexts.

Visualization, Insights and Communication:

• Proficiency in data visualization and business intelligence tools such as Tableau and Power BI.
• 3 or more years of experience designing and developing interactive dashboards and executive level reports.
• Strong understanding of human centered design principles and best practices for data and analytics experience design.
• Ability to translate complex analytical insights into clear, actionable business recommendations for senior executives and clients.

Leadership, Delivery and Ways of Working:

• Experience supporting or leading resource allocation and staffing decisions across multiple concurrent analytics initiatives.
• Strong project and program management skills, with the ability to manage multiple priorities and meet tight deadlines.
• Experience working in or leading Agile and cross functional teams.
• Demonstrated ability to mentor and develop talent, promote best practices, and foster a collaborative, high performance culture.
• Proven ability to quickly learn, adapt, and apply new analytical techniques and technologies.

Mindset and Communication:

• Strong interest and curiosity in the future of payments, credit, and digital commerce.
• Excellent verbal and written communication skills, with strong organizational and stakeholder management capabilities.
• Results oriented, data driven, and comfortable operating in complex, fast paced environments.
• Strong teamwork, relationship building, and interpersonal skills.

Languages:

• Fluency in English and Portuguese required, both spoken and written.
• Spanish proficiency is a plus.

• 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.