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.

Visa has the world’s largest consumer payment transaction dataset.  We see data on over 200 billion transactions every year from all over the world. We use that data to help our clients in the payment ecosystem grow their businesses and to help consumers access a fast, safe, and rewarding payment experience. Visa Predictive Modeling (VPM) team develops and maintains predictive machine learning models to primarily support Visa Risk and Identity Solutions. Using VisaNet data and leveraging Machine Learning (ML) and Artificial Intelligence (AI), our model scores help Visa clients all over the world for fraud defense, identity verification, smart marketing, etc. Through our models and services, VPM fuels the growth of Visa clients, generates, and diversifies revenues for VISA, while improving Visa Card customer experience and their financial lives.

Within VPM, the Acceptance Risk Model Team is responsible for developing real-time fraud detection models serving merchants. We leverage a set of rich data available at merchant check-out including transactional, digital and identity information to detect and stop fraud.

This is a Technical (Individual Contributor) role.  Your responsibilities include:

• Building and validating predictive models with advanced machine learning techniques and tools to drive business value, interpreting, and presenting modeling and analytical results to non-technical audience.

• Conducting research using latest and emerging modeling technologies and tools (e.g., Deep Neural Networks, RNN, LSTM, etc.) to solve new fraud detection business problems like enumeration attacks and/or improve existing production models’ performance.

• Improving the modeling process through MLOps and automation to drive efficiency and effectiveness.

• Partnering with a cross functional team of Product Managers, Data Engineers, Software Engineers, and Platform Engineers to deploy models and/or model innovations into production.

• Managing model risks in line with Visa Model Risk Management requirements.

• Conducting modeling analysis to address internal and external clients’ questions and requests.

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.

Basic Qualifications

• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications

• 6 or more years of work experience with a Bachelor’s degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD in a quantitative or engineering field.
• 3 or more years of experience with modern machine learning framework and tools like Gradient Boosting (e.g., XGBoost), and modern Deep Neural Network framework (e.g. RNN, LSTM, Transformer) and tools (e.g., PyTorch, TensorFlow).
• 3 or more years of experience with production model development, implementation, and support.
• Experience with Payment Fraud models.
• Experience in Agile Development and tools.
• Proven ability to quickly learn and apply new tools and techniques.
• A strong innovation leader yet a practitioner to create tangible business value balancing business objectives and technological constraints.
• Must be a team-player and capable of handling multi-tasks in a dynamic environment.
• Excellent business writing, verbal communication, and presentation skills to technical and non-technical audiences.

Technical Qualifications

• Proficiency in Python, Hadoop, Hive, Spark for big data analysis and modeling
• Experience with script and shell programming in Unix/Linux
• Experience with using GitHub and Jira for data science projects

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/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.

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.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 139,800.00 to 202,750.00 per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.