Visa Rules, Compliance and Standards (RCS) is a global group that is tasked with the role of upholding the security and integrity of Visa’s payment ecosystem. This is achieved through the deployment of rules and/or compliance standards. This team works with internal and external stakeholders to further its charter and initiatives.
This position is ideal for an experienced Senior Data Scientist who is passionate about collaborating with business and technology partners in solving challenging data science problems. You will be a key driver in the effort to define the shared strategic vision for the RCS team 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 SME who can 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 data science and software engineering skills. The candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.
Essential Functions
- As a senior data scientist in RCS team, you will help design, enhance, and build next generation fraud detection solutions in an agile development environment.
- Develop ongoing Management Information Systems (MIS) that provides oversight in Visa Ecosystem Risk Programs activity, including trends and discovery tool effectiveness.
- Translate business problems into technical data problems while ensuring key business drivers are captured in collaboration with product stakeholders.
- Independently manage data science projects with minimal supervision, while collaboration with business and technical stakeholders
- 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 unstructured 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
- Guide and manage other team members on the methodology for key solutions
- Able to work on multiple projects and initiatives with different/competing timelines and demands
- Effectively communicate status, issues, and risks associated with the projects in a precise and timely manner
- Mentor the India-based Risk COE team that is dedicated to MIS and Analytics for the program
- Build-out Visa Transaction Laundering Detection models, leveraging AI/ML, that are targeted to the various merchant activities covered under the program
Basic Qualifications:
- 5 or more 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
- Bachelors or Masters 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 exposure to modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks
- Expert in leading-edge areas such as Machine Learning, Stream Computing and MLOps
- Experience with Python and SQL on data and analytics solutions
- Excellent understanding of algorithms and data structures
- Experience with data visualization and business intelligence tools like Tableau or Power BI
- 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
- Ability to work with internal product development and engineering teams to deliver products on schedule and with great quality. Comfortable in a heavily matrixed organization
- Strong analytical and problem-solving abilities, ability to use hard data and metrics to back up assumptions and evaluate outcomes
- Ability to juggle multiple priorities and make things happen in a fast-paced, dynamic environment
- Ability to understand both business and technical concepts
Preferred Qualifications:
- Real world experience using Hadoop and the related query engines (Hive / Impala)
- Experience with Big Data and analytics leveraging technologies like Hadoop, Spark, Scala, and MapReduce
- Experience with Natural Language Processing, Generative AI and Deep Learning algorithms is a plus
- Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus
- Modeling experience in card industry or financial service company using for fraud, credit risk, payments is plus
- Experience in developing large scale, enterprise class distributed systems of high availability, low latency, & strong data consistency
- Ability to fully understand technical architecture, APIs and overall system design
- Experience in working with agile lifecycle and/or tracking and process management tools, e.g., JIRA
- Strong storytelling skills using PowerPoint presentations is a plus
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.
