Manager, Data Science

Posted 22 Hours Ago
Be an Early Applicant
São Paulo
7+ Years Experience
Fintech • Information Technology • Payments
Join a world leader in payments and technology!
The Role
The Manager of Data Science will develop strong client relationships, lead data analysis using various tools, ensure the quality of machine learning solutions, manage large datasets, create insightful reports, and leverage Generative AI tools to enhance team efficiency while aligning machine learning projects with business objectives.
Summary Generated by Built In

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

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.

The ideal candidate for the Machine Learning Solutions within MLOPs is a talented professional capable of developing state-of-the-art 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, 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
• 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 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, and financial analysis are also 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

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.

Top Skills

Hadoop
Presto
Pyspark
SAS
SQL
The Company
HQ: San Francisco, CA
26,500 Employees
On-site Workplace
Year Founded: 1958

What We Do

At Visa, we are driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. As our products and technology have evolved with the world, Visa remains ubiquitous, reaching new customers in new and often invisible ways. We are at the center of this digital revolution with a network that connects people with over 80 million businesses all over the world. And Visa’s network is expanding, accelerating our growth. Our resilient business model, with its strong track record of success, will provide you with amazing opportunities to grow in your career, as well.

We are looking for people like YOU. Come join a people-centric company where you can invest in your career.

For more information, visit visa.com/about, visacorporate.tumblr.com and @VisaNews on Twitter.

Why Work With Us

Our employees are our company. Creating an inclusive and diverse workplace has been our key priority. With our purpose to “uplift everyone, everywhere” as our guide, we’re building an environment where diverse backgrounds and perspectives are celebrated and drive success inside our company and out in our communities.

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