Machine Learning Engineer (Risk)

SHIELD is the world's leading risk intelligence company, empowering online businesses to stop fraud, build trust, and drive growth. Powered by the latest AI technology, SHIELD combines cutting-edge device fingerprinting with its proprietary Global Intelligence Network to detect new and unknown fraud threats in real time. SHIELD offers a range of solutions that span device fingerprinting, enterprise-grade protection, ad fraud prevention, and alternative credit risk intelligence. With offices across the globe and customers on every continent, SHIELD is rapidly achieving its global mission - to be the shield that enables trust for the world.

Responsibilities

As a Machine Learning Engineer (Risk), you will develop and leverage innovative machine learning solutions to solve complex sets of problems and applications. By analyzing and detecting patterns in vast amounts of data, you will have a good understanding of machine learning life cycle-algorithms, data structures and design patterns. We are looking for talented and passionate Software Engineers who are proactive in identifying problems and have the logical thought process and skills to solve them. There will be many opportunities to explore new tech stacks and to work on advanced technologies.

• 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 5 years of experience
• 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