Sr. Data Scientist

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

• As a Sr Data / 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 VERA, Visa Research, AI Platform, Operations, and Infrastructure (O&I), security and platform teams.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

Basic Qualification
•8 or more years of relevant work experience with a Bachelor Degree or 7 or
more relevant years of experience with an Advanced Degree (e.g. Masters,
MBA, JD, MD) or 3 or more years of experience with a PhD

Preferred Qualification
•Expert in leading-edge areas such as Machine Learning, Deep Learning, Stream
Computing and MLOps
•High level of competence in Python, Perl, Java, Scala, and/or Unix/Linux scripts
highly preferred
•Extensive experience with SAS/SQL/Hive for extracting and aggregating dat
•Experience with Big Data and analytics leveraging technologies like Hadoop,
Spark, Scala, and MapReduce
•Deep learning experience working with TensorFlow and Natural Language
Processing experience are highly preferred.
•Experience with one or more common statistical tools such SAS, R, KNIME,
Matlab
•Experience in developing large scale, enterprise class distributed systems of
high availability, low latency, & strong data consistency
•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.