Job Description

Company Description

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 data scientist 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 right candidate will possess 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.

A successful candidate is 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 Generative 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.

Essential Functions

As a Data 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 data 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 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:
5+ years of relevant work experience with a Bachelor\'s 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, OR 8+ years of relevant work experience.
Relevant coursework in modeling techniques such as logistic regression, Na\xc3\xafve 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
Passionate about delivering zero defect code that meet or exceed the proposed defect SLA and have high sense of accountability for quality and timeliness of one\'s own deliverables and team deliverables
Be systematic and be able to do deep research wanting to uncover the details
Have good work ethics, and be a team player to bring the best results as a team
You have the passion to understand people and always strive to improve our products
Highly driven, resourceful and results oriented
Demonstrated ability to lead and navigate through ambiguity
While you\'ll have the skill to see and understand the big picture, you\'re able to stay focused on the task at hand to achieve immediate goals

Preferred Qualifications:
6 or more years of work experience with a Bachelors 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 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
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

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.

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