Director, Synthetic Data - Data & AI Platform

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’s Data and AI Platform is a core underlying engine for all critical applications at Visa. It supports over a billion-transaction processing in real time daily and the clearing and settlement of trillions of dollars annually. A key part of the platform is its AI system. Artificial Intelligence and Machine Learning (AI-ML) have proven highly effective for generating predictions, deriving deep insights, and solving sophisticated business and technology problems across many areas at Visa. In 1993, Visa pioneered the use of tree-based and neural network-based predictive modeling techniques for real-time, risk-based fraud analytics for Advanced Authorization. Today, Visa has over 300 models with over 60 real time models that solve complex payments issues and deliver high value to our clients, all within milliseconds.

We are now entering an era of exponential advancement in AI-powered technologies. The advent of Synthetic Data has emerged as a recent innovation, allowing for faster generation and analysis of artificial datasets. This technology promotes the development of cost-effective models for data evaluation while preserving privacy and adherence to data compliance regulations. By leveraging synthetic data, our objective is to improve fairness, mitigate bias, and bolster the robustness of our machine learning systems. Visa is perfectly positioned to pioneer and lead in this emerging technology – Come join us in working on the cutting edge!

As a Director of Synthetic Data, you will report to the Senior Vice President (SVP) of Data & AI.

Essential Functions:

• Creating advanced algorithms, techniques, and frameworks for generating large-scale synthetic data.

• Developing AI and GenAI models tailored for domain-specific synthetic data, which can be further fine-tuned for diverse applications.

• Design and implement synthetic data generation processes to protect sensitive data.

• Deploying synthetic data models into test environments.

• Create AI/ML models integrating synthetic data into machine learning workflows.

• Provide leadership, mentorship, and management to Data Engineering teams, focusing on developing and maintaining robust, scalable AI platforms and capabilities.

• Deliver strategic guidance for Visa, its clients, partners, and the broader industry.

• Collaborate across the organization with teams such as Product, Applied AI, and Data Engineering

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

Basic Qualifications:
• 10 or more years of relevant work experience with a bachelor’s degree or 8 years of relevant work experience with an Advanced degree (e.g., Masters/MBA/JD/MD) or 3 years of relevant work experience with a PhD.

Preferred Qualifications:
• 12 or more years of relevant work experience with a bachelor’s degree or 8-10 years of relevant work experience with an Advanced degree (e.g., Masters/MBA/JD/MD) or 6+ years of relevant work experience with a PhD.
• Master’s or PhD in Artificial Intelligence, Computer Science, Computer Engineering, Data Science, Machine Learning, Mathematics, Statistics, or a related field from an accredited institution.
• Expertise in AI programming languages and frameworks, such as Python, Java, R, and C++.
• Experience in the creation, acquisition, cleaning, and analysis of data used to generate models for detecting deepfakes in various formats, including video, image, audio, and text.
• Experience and understanding of random sampling, data augmentation, and generative adversarial networks (GANs).
• A strong research background in AI and ML, evidenced by publications in top-tier conferences or journals.
• Familiarity with AI & ML platforms, tools and libraries, and comfort with adopting new technologies as they emerge.
• Proficiency in cloud-based AI solution