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.
Are you skilled at turning hard numbers into compelling stories and useful strategic insights? Do you solve complex data challenges with creative flair? Put those skills to work answering strategic questions for one of the world's most respected and innovative payments companies.
In this role, you will be responsible for a range of duties from basic data analytics, to implementing and delivering advanced machine learning models, visualization solutions and high impact business projects. You will get chance to leverage your business acumen, programming skills, technical knowledge of big data and machine learning techniques. This function is critical in building market-relevant fraud solutions for our clients and intellectual property for Visa.
The position will be based at Arlington, Virginia
Essential Functions
Develop state of the art machine learning models for feature extraction and classification of transactional data for risk analysis
Execute model implantation and performance tracking for risk models; generate performance analysis at the aggregate level, as well as issuer level. Interpret and present performance results to non-technical audience.
Compile complex predictive model packages for production deployment; support model installations, and monitor and calibrate production models
Propel analytic product development via conducting statistical analyses on various data sources; and add values to products by being innovative and applying the analysis
Find opportunities to create and automate repeatable analyses or build self-service tools for business users
Support sales and marketing efforts with sound statistical and financial analysis; execute ad-hoc analyses to meet the fast-changing market demands
Conduct transaction data analyses with Hadoop/Cloud and big data technologies for internal and external product owners, and develop deeper insights into the products using advanced statistical methods
Ensure project delivery within timelines and meet critical business needs
Promote big data innovations and analytic education throughout the Visa organization
Basic Qualifications
2 years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
Preferred Qualifications
Work Hours
This position requires the incumbent to be available during core business hours
Travel Requirements
This position requires the incumbent to travel for work less than 10% of the time.
Physical Requirements
This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers, reach with hands and arms, and bend or lift up to 25 pounds.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.