About The Position

The Business Intelligence Engineer occupies a unique role at the intersection of technology, marketing, finance, statistics, data mining, and social science. We provide the key insight into customer behavior necessary to guide the evolution of business strategy. With our client, understanding customer behavior is paramount to our success in providing customers with convenient, fast free shipping in the US and international markets. As a Business Intelligence Engineer you will work with our world-class marketing and technology teams to ensure that we continue to delight our customers. You will meet with business owners to formulate key questions, leverage Client’s vast Data Warehouse to extract and analyze relevant data and present your findings and recommendations to management in a way that is actionable. We seek candidates who are passionate about data analysis and data-driven decision making, uncompromisingly detail oriented, smart, efficient, and driven to help our business succeed by providing key insights that translate into action.

Requirements

  • 3-6 years of experience working with large-scale complex datasets
  • Strong analytical mindset, ability to decompose business requirements into an analytical plan, and execute the plan to answer those business questions
  • Strong working knowledge of SQL
  • Background (academic or professional) in statistics, programming, and marketing
  • Excellent communication skills, equally adept at working with engineers as well as business leaders

Nice To Haves

  • Graduate degree in math/statistics, computer science or related field, or marketing is highly desirable.
  • SAS experience a plus

Responsibilities

  • Evaluation of the performance of program features and marketing content along measures of customer response, use, conversion, and retention
  • Statistical testing of A/B and multivariate experiments
  • Design, build and maintain metrics and reports on program health
  • Respond to ad hoc requests from business leaders to investigate critical aspects of customer behavior, e.g. how many customers use a given feature or fit a given profile, deep dive into unusual patterns, and exploratory data analysis
  • Employ data mining, model building, segmentation, and other analytical techniques to capture important trends in the customer base
  • Participate in strategic and tactical planning discussions
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