Are you driven to leverage your strong quantitative analysis and skills to solve complex and large-scale challenges? This job for you! Amazon's Recruiting Technology (RT) Team is looking for motivated individuals with strong analytical skills to help drive the expansion of Amazon globally. The RT team is responsible for the architecture, design, implementation and delivery of systems that touch the entire organization. The team is creating an industry leading candidate experience; developing, building, and innovating global, scalable recruiting technology solutions that are intelligent, powerful and light-weight. This team and the technologies we own are critical for Amazon's continued growth and launching of new products and services.
You will design, evangelize, and implement solutions to address complex, business questions using advanced statistical techniques, experimentation, and big data. You will work with business and tech leaders to conduct statistical analyses, develop data pipelines, build ML models, build tools to drive continuous experimentation, and provide recommendations based on data analyses. We are looking for creative thinkers who can combine a strong analytical toolkit with a desire to continue innovating, and who is able to execute and deliver on big ideas.
The ideal candidate will demonstrate deep understanding of statistical and machine learning concepts, technical skills for leveraging analytical tools to solve large scale problems, technical aptitude to remain abreast with data science related technologies, leadership in charting new analytical courses, and excitement to take iterative approaches to tackle long-term challenges. The successful candidate will have good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders across Amazon.
Amazon is an Equal Opportunity Employer - Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.BASIC QUALIFICATIONS
• M.S. or equivalent in Statistics, Mathematics, Engineering, Computer Science, or related analytical disciplines.
• Deep understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc.
• Experience using statistical, simulation, visualization, and machine-learning tools and commercial packages
• Experience with big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via AWS technologies, SQL, and data pipelines
• Experience one or more programming languages (e.g. Python, Java, C++, etc.)
• Familiarity with some of the clustered data processing tools such as Hadoop, Spark, Map-reduce, and Hive
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.PREFERRED QUALIFICATIONS
• Ph.D. in Statistics, Mathematics, Engineering, Computer Science, or related analytical disciplines
• Experience in developing machine-learning algorithms, statistical and mathematical optimization models, and simulation and visualization tools
• Experience with ensemble models and with clustered data processing tools such as Hadoop, Spark, Map-reduce, and Hive
Experience with agile or scrum methodology