Manager, Data Science

**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**:
Visa Consulting and Analytics (VCA), the consulting arm of Visa, is a global team of industry experts in strategy, marketing, operations, risk and economics consulting, with decades of experience in the payments industry.

Our VCA teams offers,
- Consulting services customized to the needs of Visa client business objectives and strategy
- Business and economic insights and perspectives that impact business and investment decisions
- Self-service digital solutions Visa clients can leverage to improve performance in product, marketing and operations
- Proven data-driven marketing strategies to increase clients ROI
- The Machine Learning Operations (MLOps) team under Data Science LAC is a multidisciplinary group responsible for designing robust data infrastructures, developing innovative machine learning solutions, enforcing data governance standards, and aligning machine learning projects with business objectives to drive business value and revenue generation in VCA LAC._

**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, SAS, 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.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
**Qualifications**

**Qualifications**:

- 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 and Portuguese (spoken/written), Spanish is a plus.

Technical Expertise:

- 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.
- Proficient in some of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, K-Means Clustering, LLM, XGBoost, etc.
- Prior experience in developing and working Tableau driven dashboards is a plus.
- Familiarity with credit risk assessment techniques, credit management