100% Remote
Pay rate range - $68/hr. to $70/hr. on W2
Required
Job Description:
- 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 (Expert Level)
Data Pipeline (expert)
Data warehousing (intermediate)
- Background (academic or professional) in statistics, programming, and marketing
- Excellent communication skills, equally adept at working with engineers as well as business leaders
Preferred
- Data Visualization
- AWS experience a plus
- S3, andies, etc.
Degree or Certification :
- Preferred Graduate degree in math/statistics, computer science is highly desirable.
Responsibilities
Understanding customer behavior is paramount to our success in providing customers with convenient, fast free shipping in the US and international markets. As a Senior 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 the vast Data Warehouse to extract and analyze relevant data, and present your findings and recommendations to management in a way that is actionable. If you are motivated to serve the needs of our customers, you will also be able to satisfy your curiosity by working with one of the world's largest datasets. 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.
Key Responsibilities
- Evaluation of the performance of program features and marketing content along with 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