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BASIC QUALIFICATIONS – 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience – 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience – Master’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor’s degree and 3+ years of professional or military experience – Ability to translate well-defined problems into data science problems. You solve these problems using appropriate assumptions, methodologies, and data science best practices – Experience applying theoretical models in an applied environment PREFERRED QUALIFICATIONS – Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive) – Knowledge of engineering practices and patterns for the full software/hardware/network development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and live site operations. – Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations Key job responsibilities • Proactively seek to identify business opportunities and insights and provide solutions to automate and optimize key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams. • Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult customer or business problems and cases in which the solution approach is unclear. • Acquire this data by accessing data sources and building the necessary SQL/ETL queries or scripts. • Build models and automated tools using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. • Validate these models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. • Implement these models in a manner which complies with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. We are open to hiring candidates to work out of one of the following locations: Amman, JOR
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