Job Description

Payments Industry is a very exciting and fast-developing area with lot of new and innovative solutions coming to market. With strong demand for new solutions in this space, it promises to be an exciting area of innovation. VISA is a strong leader in the payment industry and is rapidly transitioning into a technology company with significant investments in this area.

If you want to be in the exciting payment space, learn fast and make big impacts, Ecosystem & Operational Risk technology which is part of Visa's Value-Added Services business unit is an ideal place for you!

In Ecosystem & Operational Risk (EOR) technology group, the Payment Fraud Disruption team is responsible for building critical risk and fraud detection and prevention applications and services at Visa. This includes idea generation, architecture, design, development, and testing of products, applications, and services that provide Visa clients with solutions to detect, prevent, and mitigate fraud for Visa and Visa client payment systems.

We are in search of inquisitive, creative, and skillful technologists to join our ranks. We are currently looking for a Director of Machine Learning who will take the lead and manage several strategic initiatives within our organization.

The right candidate will possess strong machine learning background, with demonstrated leadership experience in driving technical architecture, design and delivery of products and services that have created business value and delivered impact within the payments or payments risk domain or similar industries.

This position is ideal for an experienced Data Science / Machine learning leader who is passionate about collaborating with business and technology partners and engineers to solve challenging business problems. You will be a key driver in the effort to define the shared strategic vision for the Payment Fraud Disruption platform and defining tools and services that safeguard Visa's payment systems.
Essential Functions:

Leverage generative AI techniques to enhance fraud detection models, creating synthetic data for robust testing and model training.
Incorporate generative AI into the machine learning strategy to introduce novel fraud detection methods and improve predictive accuracy.
Utilize generative AI to simulate potential fraud scenarios, aiding in the development and refinement of fraud prevention solutions.
Implement generative AI tools to facilitate communication and alignment between technical teams and business stakeholders, ensuring a shared understanding of goals.
Define and drive the machine learning strategy for fraud prevention solutions.
Align ML initiatives with Visa's broader business and technology objectives in the payments risk space.
Lead the design, development, testing, and deployment of ML/DL models to detect and prevent payment fraud.
Supervise model refresh cycles, experimentation, and continuous improvement.
Partner with product managers, engineers, and business stakeholders to ensure alignment between technical and business goals.
Work closely with support teams to troubleshoot production issues tied to models and pipelines.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications
• 10+ years of relevant work experience with a Bachelor's Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.

Preferred Qualifications
• 12 or more years of work experience with a Bachelor's Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
• 10+ years of relevant work experience and a Bachelors degree, OR 13+ years of relevant work experienceExperience leading development, delivery and deployment of ML / DL models, feature engineering, model refresh, and experimentation.Experience leading product development & delivery of AI/ML solutions, applied to real-world problemsExperience leading design and development of mission-critical, secure, reliable systemsExcellent understanding of algorithms and data structuresExcellent problem solving and analytics skills. Capable of forming and advocating an independent viewpointStrong experience with agile methodologiesExcel in partnering with Product leaders and technical product managers on requirements workshops, helping define joint product/technology roadmaps & driving prioritizationExperience driving continuous improvements to processes/tools for better developer efficiency and productivityDemonstrated ability to drive measurable improvements across engineering, delivery and performance metricsDemonstrated success in leading high performing, multi-disciplinary and geographically distributed engineering teams. Demonstrated ability to hire, develop and retain high-caliber talentMust demonstrate longer-term strategic thinking and staying abreast with latest technologies to assess what's possible technicallyStrong collaboration and effective communication, with focus on win-win outcomes
• Visa is not offering relocation assistance for this role

U.S. Applicants Only
The estimated salary range for this position is $214,500.00 to $ 343,400.00 USD 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.

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.