Anti-Fraud Risk Engineer

Company Description Our Client, is an award-winning workplace. They have been recognized by Comparably as #1 CEO, Company Happiness, Benefits, Compensation, Diversity, and more! Not to mention they’ve been awarded by Glassdoor as the 2nd Best US workplace & Best Large Company US CEO in 2018, Wealthfront, and Business Insider. They culture focuses on delivering happiness, our commitment to transparency, and the tangible benefits we provide our employees and our customers.

Job Description

POSITION TITLE: Anti-Fraud Risk Engineer LOCATION: Phoenix AZ SALARY: Based on Experience SPONSORSHIP: No

Responsibilities:

• Teamwork with different function teams to design abuse, porn, tele-fraud detection model base on different business product requirement and protection policy.
• Responsible for developing telephone anti-fraud, anti-spam, anti-pornography, anti-abuse registration and other services
• Responsible for the implementation and practice of related algorithms under the current mainstream stream computing platform

Qualifications

• Master’s degree + 2 years working experience in machine learning
• Proficiency in at least one programming language such as Java, Python
• Proficiency in big data, the use of frameworks related to stream computing, such as Spark, Flink, etc. And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc.
• The basic algorithms and deep learning algorithms of related machine learning have a deep understanding and mastery, and require the use of related algorithms, experience in the processing of common procedures in feature engineering, and excellent engineering practice capabilities
• Experience in algorithms such as, anti-fraud, telecommunication risk control, recommendation system, advertising orientation, click model, etc. is preferred
• Strong research capabilities, such as high-quality papers published in the field ** conferences such as CVPR, ICCV, ICML, NIPS, etc.
• ACMICPC, NOI / IOI, Top coder, Kaggle competition winners are preferred
• Research experience related to graph learning and few-shot learning is preferred
• Language requirement: English, Mandarin is plus

Additional Information All your information will be kept confidential according to EEO guidelines.