Overview
SHIELD is a device-first fraud intelligence platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activity.
Powered by SHIELD AI, we identify the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence, empowering businesses to stay ahead of new and unknown fraud threats.
We are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more.
With offices in LA, London, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.
Responsibilities
Ability to design and develop machine learning algorithms
Discover, design, and develop analytical methods to support novel approaches of data and information processing
Identify and apply appropriate methods to process and analyze large data-sets of labelled and unlabeled records, and discover new valuable insights for the system
Provide support on other part of the system (not limited to Machine Learning)
Conduct software performance analysis, scaling, tuning and optimization
Review and contribute to improve current software and system architecture for stability and to optimize performance
Research & development of fraud detection solution
Requirements
Minimum Bachelor Degree in Computer Science, Information System with Machine Learning specialization or equivalent
Strong foundation in database and data scaling
Experience with various Machine Learning algorithms and ability to apply in real life cases
Experience in MySQL, NoSQL and Columnar database
Experience in C++, C, Python and other programming languages will be an advantage
Prior experience in e-payments or e-commerce industry is a plus
Strong analytical, interpersonal, communication and presentation skills
Seniority level
Associate
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Non-profit Organizations and Primary and Secondary Education
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