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Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud? Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide.
Job Responsibility
Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference
Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection
Use machine learning and analytical techniques to create scalable solutions for business problems
Identify new areas where machine learning can be applied for solving business problems
Partner with developers and business teams to put your models in production
Mentor other scientists and engineers in the use of ML techniques
Requirements
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience building machine learning models or developing algorithms for business application
Nice to have
Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms