Data Science Manager

Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

Data Science Manager

As the world’s leader in digital payments technology, Visa’s mission is to connect the world through the most creative, reliable and secure payment network – enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company’s dedication to innovation drives the rapid growth of connected commerce on any device and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.

At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.

You’re an Individual. We’re the team for you. Together, let’s transform the way the world pays.

Job Description

The ideal candidates are problem solvers, equipped with strong analytical & quantitative skills suited to address key strategic needs for Visa’s clients by building analytical components and data solutions.

Adepts of a creative and critical thinking, they are able to deconstruct problems and transform insights into large scale, state-of-the-art solutions. Candidates must be quick learners with a strong sense of personal responsibility.

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 deploy analytical solutions.
• Lead quality assurance (QA) activities from design to implementation phase of the proposed analytical solutions.
• Manage large volumes of data, extract, analyze and manipulate large datasets using standard tools such as Hadoop Ecosystem, PySpark, SAS, Presto, SQL, etc.
• 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.
• Interacting with several stakeholders for the strategic definition of priorities.
• Continuously develop and present innovative ideas in order to improve current business practices within Visa.
• Communicate complex concepts and the results of the analyses in a clear and effective
  manner.
• Support technical knowledge transfer to facilitate implementation of the business
  solution developed by leading internal workshops and small training sessions.
• Document all the projects developed and write other documentations as needed.

Travel Requirements

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

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 two days a week, Tuesdays and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.                                                                                                                                                            

Qualifications

• BA/BS required, Master's degree preferred (e.g., Statistics, Computer Science, Engineering or related fields).
• 8+ years of overall experience with a preferred minimum of 5 in retail banking, payments, financial services, and/or technology industries.
• Proven Hands-on experience in advanced analytics and statistical modeling including Linear Regression, Logistic Regression, Clustering methods (e.g. K-means), Classification methods (Decision Trees/Random Forest), among others.
• Experience working with large volumes of data (Big Data) is a must, extracting, cleaning and manipulating large datasets using standard tools such as Python/PySpark, SQL, Hadoop/Hive, Presto, etc.
• Knowledge of visualization tools such as Tableau or PowerBI.
• Excellent project management, organizational and presentational skills.
• Strong teamwork, relationship management and interpersonal skills.
• Ability to multi-task various projects while meeting required deadlines.
• 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.