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Job ID 
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ADCI - Karnataka
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Job Description

Amazon’s Worldwide Consumer Marketing organization (also referred to as ‘Traffic’) invites customers to visit and purchase from Amazon’s retail sites through highly personalized messages delivered via all available large scale communication channels—both free and paid. The organization builds, operates, and improves the technology platforms that power all marketing communications and manages all actual campaigns; message prioritization and marketing spend decisions. Consumer Marketing consists of a series of single-threaded technology and business teams, each of which owns the entirety of a channel of communication or customer segment: natural and paid search (i.e. SEO and SEM), affiliate networks (Associates), display advertising, email, browser integration, and mobile marketing. The organization is also home to teams that conceive, build and operate great customer experiences on and off-site, designed specifically to attract customers to Amazon. These features drive shopping visits, but also build daily shopping habits, generate trials in new and different product categories and programs, and encourage customers to visit Amazon directly rather than through intermediaries. Among these teams are those overseeing Amazon’s efforts in Free/Earned Social Media, Amazon’s Deals offerings (the Amazon Goldbox and more), Holiday and other periodic on-site shopping Events, and AmazonSmile, the recently launched mirror version of—which allows customers to shop on behalf of their choice from among nearly a million registered nonprofit organizations. Consumer Marketing Analytics is a central organization that builds predictive analytical solutions for all marketing channels and strategic programs across Consumer business. Consumer Marketing Analytics team is working on several machine learning problems related to customer forecasting, segmentation, predictive modeling and analytics. We analyze and process terabytes of data on a daily basis. We extensively use Hadoop, Pig, Hive, AWS services such as SWF, S3, EMR, DynamoDb etc. We have built several machine learning models which are used to power various consumer experiences both onsite as well as off site.

We are looking for an outstanding individuals who combine superb technical, communication, and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. The ideal candidate for our team is a thinker and a doer: someone who loves sophisticated algorithms and mathematical precision, but at the same time enjoys implementing real systems, and is motivated by the prospect of spectacular business returns. A successful team member will be skilled at anticipating bottlenecks, making tradeoffs between the business needs versus technical constraints and encouraging risk taking behavior to maximize business benefit. They are able to focus heavily on cross functional communication to ensure key decisions and status surrounding projects are clear to all. If you like solving hard problems, wearing multiple hats, and like working with people that do the same, we invite you to apply. In joining our team, you'll enjoy a competitive salary, great benefits, a creative and comfortable work environment, and the exciting opportunity to be part of a fast-paced and growing technology company.

Basic Qualifications

  • PhD in CS or Math, Machine Learning, Operational research, Statistics or in a highly quantitative field. (PhD strongly preferred).
  • 5+ years of industrial experience in predictive modeling and analysis, predictive software development
  • Strong Problem solving ability
  • Good skills with Java or C++, Perl/Python (or similar scripting language)
  • Experience in using R, Matlab, or any other statistical software
  • Experience in mentoring junior team members, and guiding them on machine learning and data modeling applications
  • Strong communication and data presentation skills

Preferred Qualifications

  • 5+ years of industrial experience in predictive modeling and analysis, predictive software development
  • Experience handling gigabyte and terabyte size datasets
  • Experience working with retail or e-commerce data
  • Experience working with distributed systems and grid computing
  • Publications or presentation in recognized Machine Learning and Data Mining journals/conferences