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

Payments is an exciting and rapidly evolving space. With strong demand for new solutions, it promises to be an exciting area of innovation. If you want to be a part of this exciting space, learn fast and make a big impact, Ecosystem & Operational Risk product development organization is the ideal place for you! Ecosystem & Operational Risk (EOR) organization is responsible for building critical risk and fraud detection and prevention applications/products for Visa and it’s clients.

Reporting to the head of EOR PD, you will play a critical role in the acceleration of our AI journey. You will be responsible for setting the AI/ML roadmap for the organization (in conjunction with business), assessing AI/ML and Gen AI initiatives & executing on these initiatives across the entire EOR organization. This includes supporting all the product development lanes in EOR, for their AI/ML initiatives. You will be a key driver in the effort to define the strategic vision for the Payment Fraud Disruption platform, in conjunction with our business partners. Additionally, you will evangelize Gen AI driven internal productivity tools to accelerate adoption in our engineering teams. You will also coach and mentor our engineering talent, to help scale the AI/ML efforts.

The candidate for this role needs to have strong AI/ML and Data Science background, with demonstrated experience in building, training, implementing and optimizing advanced AI models for payments, risk or fraud prevention products that created business value and delivered impact within the payments or payments risk domain or have experience building AI/ML solutions for similar industries.

To be successful in this role, the candidate needs to be a technical leader with the ability to engage with business and technology partner be able to think broadly about Visa’s business and drive solutions that will enhance the safety and integrity of Visa’s payment ecosystem. The ideal candidate will bring the excitement and passion to leverage Generative AI to advance existing fraud detection mechanisms and to innovate and solve new fraud use cases. The candidate will help deliver innovative insights to Visa's strategic products and business. This candidate needs to have strong academic track record and be able to demonstrate excellent software engineering skills. The candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.

Essential Functions

· Architect, design, enhance, and build next generation fraud detection solutions. You will support all the product engineering lanes of EOR, with their AI/ML initiatives.

· Drive the architecture for key cross team / cross product AI/ML projects (via architecture/design documents and developing code key modules).

· Collaborate with product stakeholders to formulate business problems as technical data-centric problems.

· Work with software engineers to ensure feasibility of solutions. Deliver prototypes and production code as needed.

· Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.

· Build needed data transformations on structured and un-structured data.

· Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, data mining and statistical techniques.

· Devise and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, A/B testing of models.

· Devise and implement methods for efficiently monitoring model effectiveness and performance in production.

· Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.

· Contribute to development and adoption of shared predictive analytics infrastructure.

· Establish software development patterns and best practices via examples and shipping code.

· Ensures that relevant project teams follow a common set of principles and patterns and utilize a standard set of technology frameworks and libraries.

· Mentor and build a high performing team of ML scientists across EOR.

· Evangelize GAI productivity tools (chatgpt, Github copilot) in EOR engineering teams and boost adoption to drive efficiencies

· Able to influence teams across EOR, across Value Added Services and across Visa

· Able to work on multiple projects and initiatives with different/competing timelines and demands.

· Present technical solutions, capabilities, considerations, and features in business terms. Communicate status, issues, and risks in a precise and timely manner

· Collaborate across multiple engineering teams within Visa - Visa Research, AI Platform, Operations and Infrastructure (O&I), CyberSecurity, Value Added Services Product Engg .

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:

• 12+ years of relevant work experience with a Bachelor’s Degree or at least 9
years of work experience with an Advanced degree (e.g. Masters, MBA, JD,
MD) or 6 years of work experience with a PhD, OR 15+ years of relevant work
experience.

Preferred Qualifications:
• 15 or more years of experience with a Bachelor’s Degree or 12 years of
experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with
9+ years of experience
• PhD in Computer Science, Operations Research, Statistics, or highly
quantitative field (or equivalent experience) with strength in Deep Learning,
Machine Learning, Data Mining, Statistical or other mathematical analysis
· Relevant coursework in modeling techniques such as logistic regression, Naïve
Bayes, SVM, decision trees, or neural networks
· Expert in leading-edge areas such as Machine Learning, Deep Learning, Stream
Computing and MLOps
· Ability to program in one or more scripting languages (such as Perl, Python)
and programming languages (such as Java, Scala)
· Excellent understanding of algorithms and data structures
· Excellent analytic and problem-solving capability combined with ambition to
solve real-world problems
· Excellent interpersonal, facilitation, and effective communication skills (both
written and verbal) and the ability to present complex ideas in a clear, concise
way
· Have great work ethics, and be a team player striving to bring the best results
as a team
· High level of competence in Python, Scala, and Unix/Linux scripts
· Extensive experience with SAS/SQL/Hive for extracting and aggregating data
· Experience working with large datasets using tools like Pig or Hive is a plus
· Experience with Big Data and analytics leveraging technologies like Hadoop,
Spark, Scala, and MapReduce
· Deep learning experience working with TensorFlow is necessary
· Experience with Natural Language Processing is necessary
· PhD degree in Computer Science or related field and 10+ years of Machine
Learning System Development Experience after PhD
· Real world experience using Hadoop and the related query engines (Hive /
Impala)
· Experience with one or more common statistical tools such SAS, R, KNIME,
Matlab
· Publications or presentation in recognized Machine Learning and Data Mining
journals/conferences is a plus
· Experience with data visualization and business intelligence tools like Tableau
· Modeling experience in card industry or financial service company using for
fraud, credit risk, payments is plus
· Proficiency in designing & solving classification/prediction problems using
open-source libraries such as Scikit learn
· Experience in developing large scale, enterprise class distributed systems of
high availability, low latency, & strong data consistency
· Experience developing instrumentation for software components, to help
facilitate real-time and remote troubleshooting/performance monitoring
· Experience in architecting solutions with Continuous Integration and
Continuous Delivery in mind
· Familiarity with in distributed in-memory computing technologies

Additional Information

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 203,800.00 to 295,600.00 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.