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.
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The fraud and risk management team within CyberSource is responsible for designing and building machine learning models for detecting, preventing and managing fraud in e-commerce payment events. The team collaborates closely with Visa colleagues and other internal stakeholders to provide the advanced and multilayered fraud and risk management solutions to enterprise as well as small-to-midsized businesses.
We are currently seeking a Data Scientist to support fraud risk modeling projects and drive insights for CyberSource. Ideal candidates for this position will have a very strong background of statistics and machine learning techniques and tools and. In addition, the candidate should have a proactive mindset for innovative researches and a highly collaborative approach to project work.
The position will be based at Visa’s office in Foster City, California. You will work collaboratively with a team composed of both data scientists and engineers to:
Build and validate risk models with advanced machine learning techniques
Support model installations, and monitor and calibrate production models
Interpret and present modeling and analytical results to all level audience
Define financial and analytic metrics to measure development and production outcomes and produce performance reports
Conduct transaction data analyses for internal and external product owners, and develop deeper insights into the products using advanced statistical methods
Support sales and marketing efforts with sound statistical and financial analysis; execute ad-hoc analyses to meet the fast-changing market demands
Drive analytic product development via conducting statistical analyses on various data sources; and add values to products by innovatively applying the analysis
Enhance existing solutions and approaches by promoting new methodology and best practices in data science field
Collaborate with internal and external stakeholders and cross-functional teams
2 years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
Graduate/Post Graduate degree (Master's or Ph.D.) in quantitative field such as statistics, mathematics, computer science, finance, economics or relevant area.
Hands-on experience in data science and analytical functions
Ability to analyze large datasets, extract information, features, anomalies,etc.
Ability to understand customer/client behavior, apply modeling and machine learning to business problems
Ability to communicate model outputs, performance internally and externally
Self-starter, curious, team player in dynamic environments.
This position requires the incumbent to travel for work up to 5% of the time.
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.