Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.
When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.
Join Visa: A Network Working for Everyone.
Payments are a very exciting and fast-developing area with a lot of new and innovative ideas 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 & Operation Risk technology which is part of Visa’s Value-Added Services business unit is an ideal place for you!
In Ecosystem & Operation Risk group, 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.
This position is ideal for an experienced ML engineer who is passionate about collaborating with business and technology partners in solving challenging fraud prevention 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.
The candidate for this role need to have strong ML and Data Science background, with demonstrated experience in building, training, implementing and optimized 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 need to be a technical leader with the ability to engage in high bandwidth conversations with business and technology partners and 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 candidate will help deliver innovative insights to Visa's strategic products and business. This role represents an exciting opportunity to make key contributions to strategic offering for Visa. 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
The ideal candidate will bring the excitement and passion to leverage Generate AI to advance existing fraud detection mechanisms and to innovate and solve new fraud use cases. This engineer will use code generation capabilities like GitHub copilot to drive efficiencies in software development.
As a Lead ML Scientist you will help design, enhance, and build next generation fraud detection solutions in an agile development environment.
Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product stakeholders.
Work with software engineers to ensure feasibility of solutions. Deliver prototypes and production code based on need.
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.
Mentor and train other ML scientists on the team on key solutions
Able to work on multiple projects and initiatives with different/competing timelines and demands.
Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner
Collaborate across engineering teams and leaders in Ecosystem& Operational Risk, Visa Research, AI Platform, Operations, and Infrastructure (O&I), security and platform teams.
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 three days a week, Tuesdays, Wednesdays, and Thursdays with a general guidepost of being in the office 50% of the time based on business needs.
•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.
•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 or Python and programming languages such as Java or 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
•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
•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
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 161,300.00 to 209,700.00 USD, 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.