Fraud Data Analyst Job Vacancy in Zoom Video Communications, Inc. San Francisco Bay Area, CA – Latest Jobs in San Francisco Bay Area, CA – updated today
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Company Name : Zoom Video Communications, Inc.
Location : San Francisco Bay Area, CA
Position : Fraud Data Analyst
Job Description : Work Styles at Zoom
In most cases, you will have the opportunity to choose your preferred working location from the following options when you join Zoom: in-person, hybrid or remote. Visit this page for more information about
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Summary:
As Zoom grows and expands the product reach, fraudulent activities become more common and fraudsters become more sophisticated. In order to stay ahead and catch fraud as close as possible to the fraud event, we need to leverage more complex analysis techniques.
This role will help us catch more fraud events, save wasted dollars, and improve Zoom’s customer experience.
Responsibilities:
Improve our fraud detection on all Zoom’s products (Zoom Phone, Zoom Meeting Audio conference) by leveraging analysis techniques to help detectors to identify fraud signals, catch, stop, and even prevent fraud
Drive reduction of fraud dollars measurable percentage in all Zoom’s products
Work with CSM/Trust&Safety/NOCs/PMs to identify known characteristics of fraudulent activity in Zoom’s Phone, Meeting audio conference side.
Implement highly optimized fraud analyzer using data analytics techniques
Extract and process real-time and batch data from Zoom services for data exploration, aggregation, and validation, Analyze emerging fraud patterns using historical data and help improve fraud detectors to proactively counter new fraudsters;
Investigate and respond to urgent internal requests to resolve ad-hoc fraud-related issues;
Communicate with partner telecom carriers to investigate external fraud alerts and resolve fraudulent use of telephony services in Zoom services
Skills:
Strong data manipulation skills including SQL and Python
Strong fundamentals in statistics
Demonstrated problem-solving mindset with analytical skills and attention to detail
Ability and willingness to be on-call in some weekends and holidays (taking turns with the rest of the team) to support Fraud systems
Nice-To-Haves:
Knowledge of MLOps frameworks such as TensorFlow Extended, Kubeflow, or MLFlow
Proficient in leveraging Spark or Flink to create and manipulate data pipelines in an AWS big data environment
Fundamentals in machine learning theories
We believe that the unique contributions of all Zoomies is the driver of our success. To make sure that our products and culture continue to incorporate everyone’s perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Zoom is proud to be an equal opportunity workplace and is an affirmative action employer. All your information will be kept confidential according to EEO guidelines.
We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records as well as any qualified applicants requiring reasonable accommodations in accordance with the law. If you need any assistance or accommodations due to a medical condition, or if you need assistance accessing our website or completing the application process, please let us know by emailing us at
careers@zoom.us
.
Zoom requires all U.S. employees who will work in person at a Zoom office, attend in-person Zoom meetings or have in-person customer meetings to be fully vaccinated. Zoom will consider requests for reasonable accommodations for religious or medical reasons as required under applicable law.
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