Manager, Visa Consulting and Analytics, Data Services Practice

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

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, digital marketing and economics, VCA solves the most strategic problems for our clients.

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.

The ideal candidate for the Data Solutions within IDS is a talented professional capable of developing state-of-the-art machine learning models, data solutions and enhancing existing ones to address complex business problems.

Responsibilities

• Develop and grow exceptional internal client relationships to define priorities and to set the solutions development strategy to be followed.

• Utilize Visanet Data and Visa’s analytical capabilities, technology, and industry expertise to develop, standardize and enhance Machine Learning Solutions.

• Lead quality assurance (QA) activities from design to implementation.

• Manage large volumes of data: extract, analyze and manipulate large datasets using standard tools such as Hadoop Ecosystem, PySpark, Presto, SQL, etc.

• Design, develop, and maintain Data Assets for scalability, extensibility, performance, and re-use.

• Work with team members to create useful reports and dashboards that provide insight, improve/automate processes, or otherwise add value to the team.

• Data Cleansing/Wrangling – This involve parsing and aggregating messy, incomplete, and unstructured data sources to produce data sets that can be used in predictive modeling or in dashboards development.

• Develop and validate advance data mining tools, algorithms, and other capabilities to solve business problems related to one or more countries in Latin America.

• Identify relevant market trends based on a deep analysis of payment industry Information.

• Leverage Generative AI Tools to increase the team’s efficiency and the knowledge sharing across the different structures.

• Continuously develop and present innovative ideas to improve current business practices within Visa.

Technical Expertise

• Proficient in some of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, K-Means Clustering, LLM, XGBoost, etc.

• Proven hands-on expertise in distributed computing environments / big data platforms (Hadoop, Presto, PySpark, etc.) as well as common database/data warehouse systems (SQL, Hive, etc.).

• Strong programming ability in different programming languages such as Python, R, Scala, Java, and SQL.

• Prior experience in developing and working Tableau driven dashboards is a plus.

• Proven hands-on experience with both common computing environments (e.g., Linux, Shell Scripting) and commonly used IDE’s (Jupyter Notebooks).

Leadership Competencies

• Demonstrates integrity, maturity, and a constructive approach to business challenges

• Serves as a role model for the organization by implementing core Visa Values

• Shows respect for individuals at all levels in the workplace

• Strives for excellence and extraordinary results

• Uses sound insights and judgments to make informed decisions in line with business strategy and needs

• Able to allocate tasks and resources across multiple lines of businesses and geographies

• Able to influence senior management both within and outside Data Science

• Successfully persuading internal stakeholders to commit to best-in-class solutions, when required

Travel Requirements

• This position may require the incumbent to travel for work 10% of the time.

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

Qualifications

Basic Qualifications
•5 or more 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

Preferred Qualifications
•Minimum of 7+ years of expertise in applying Machine Learning solutions to
business problems – model development and production experience required.
•Post-graduate degree in a quantitative field such as Statistics, Mathematics,
Data Science, Operational Research, Computer Science, Informatics,
Economics, or Engineering (Master or PhD preferred).
•Deep understanding of Payments and the Banking industry, including card
verticals such as consumer credit, consumer debit, prepaid, small business,
commercial and co-branded products.
•Expert knowledge of data, market intelligence, business intelligence, and AI-
driven tools and technologies, with demonstrated ability to incorporate new
techniques to solve business problems.
•Experience in presenting ideas and analysis to stakeholders, tailoring data-
driven results to various audience levels.
•Proven ability to deliver results within committed scope, timeline, and budget.
•Fluency in English (spoken/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.