Staff Data Scientist AIML Python
Staff Data Scientist AIML Python
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Job Description
In Ecosystem & Operational 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.
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 Visas business and drive solutions that will enhance the safety and integrity of Visas payment ecosystem.The candidate will help deliver innovative insights to Visas 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 selfstarter 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.
Essential Functions
As a Staff 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 inhouse and thirdparty 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.
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 23 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 Bachelors 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.
Preferred Qualifications:
6 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
Expert in leadingedge 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 inmemory 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.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
