Product Analytics Manager, Ecosystem Risk Programs

Ecosystem Risk Programs is a Global Risk group that is tasked with the role of upholding the security and integrity of the payment ecosystem through the interdiction of illegal and fraudulent activity.  This is achieved through the deployment of risk quality control and/or compliance programs.  The programs are deployed through Visa Rules and additional client guidelines and Visa performs quality control leveraging proprietary tools, specialized third party vendors, regional risk teams, and other stakeholders. ERP also works with internal and external stakeholders to further its charter and initiatives.

This position is ideal for an experienced Senior Data Scientist and Reporting SME who is passionate about collaborating with business and technology partners in solving challenging problems involving illegal and fraudulent activity. You will be a key driver in the effort to define the shared strategic vision for the Ecosystem Risk Programs 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. The candidate should be proficient in performing detailed analyses and deep-dive investigations on large volumes of data.

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 and data investigator in ERP 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 analytics 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.
• Translate data investigations and analyses into actionable business intelligence.
• 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
• Build-out Visa Transaction Laundering Detection models, leveraging AI/ML, that are targeted to the various merchant activities covered under the program
• Help manage the India-based Risk COE team responsible for the MIS and Analytics for the program

Basic Qualifications:

• 6 or more years of relevant work experience with a Bachelor’s Degree or at least 4 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) 
• 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, Deep Learning, Stream Computing and MLOps
• Experience with Python, SQL, PySpark and Hive 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
• Outstanding communication and presentation skills
• Ability to understand both business and technical concepts
• Strong hold on MS Excel and PowerPoint

Preferred Qualifications:
 

• High level of competence in Python, Spark, and Unix/Linux scripts
• Real world experience using Hadoop and the related query engines (Hive / Impala)
• Extensive experience with SAS/SQL/Hive for extracting and aggregating data
• Experience with Big Data and analytics leveraging technologies like Hadoop, Spark, Scala, and MapReduce
• Experience with Natural Language Processing 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
• Own delivery of multiple projects from technical requirements and quality assurance perspective.
• 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
• Self-starter who can communicate with a deep understanding of the company needs and enable people to move forward through complexity
• Demonstrated cross-functional competence, having led/coordinated teams across functional areas in large, matrixed organizations
• Flexible and creative thinker with strong execution skills, generate out-of-the-box solutions, manage ambiguity, anticipate the impact of decisions/initiatives and able to move seamlessly from high level concepts to details

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.