At Amazon we're aiming to be the most customer-centric company on Earth. To get there, we need exceptionally talented, bright, and driven person who can help take our Customer Service to to the next level.
We are looking for a dynamic, resourceful, and organized Business Intelligence Engineer (BIE) to join our EU Customer Services Insights function.
This is a unique, high visibility opportunity for someone with a passion to dive deep into disparate, large-scale data sets across the business, to surface unique insights to business partners and leaders.
You will impact the way Amazon interacts with our Customers at all levels.
The ideal candidate will have excellent analytical abilities, outstanding business acumen and judgment, intense curiosity, strong technical skills, and superior written and verbal communication skills.
They will be a self-starter, comfortable with ambiguity, able to think big and be creative (while paying careful attention to detail), and enjoy working in a fast-paced dynamic environment.
To be successful in this role, you should have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards and using visualization tools, while always applying analytical rigor to solve business problems.
Successful candidates will also have good working knowledge of computing statistical and mathematical modelling, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems.
The successful candidate will be a key member of the EU Customer Experience and Insights (CXI) team which consists of Program Managers, Business Analysts, BIEs and Data Scientists.
Key Responsibilities :
Responsibility includes but is not limited to :
Translate complex or ambiguous business problem statements into analysis requirements
Proactively and independently work with stakeholders to define analytical approach and construct use cases connecting data from several different business units
Build knowledge on data and metrics of the wider business for providing the big picture on the customer experience and how it translates into business metrics
Solve ambiguous analyses with less well-defined inputs and outputs; drive to the heart of the problem and identify root causes
Derive recommendations from analysis that significantly impact a department, create new processes, or change existing processes
Work with a variety of data sources and large data sets, pull data using efficient query development and provide a holistic and consistent view of the data
Provide insights through basic statistical measures such as hypothesis testing for improvement initiatives
Actively drive automation of data requirements by scaling data processes and create self-service tools
Communicate complex analytical insights and business implications effectively
Actively manage the timeline and deliverables of projects, anticipate risks and resolve issues
Propose and build a future-proof data architecture, enabling flexible and reliable self-service
Bachelor’s degree in Business Administration, Finance, Computer Science, Statistics, Economics, Engineering or any related field from an accredited institution
2+ years’ experience as a BIE
Proficient with analysis programming languages and statistical software, i.e. SQL, Tableau, Excel, R and usage of tools like Excel, Tableau, COGNOS, Microstrategy, Quicksight
Experience working with complex data sets in data warehouse environments
A proven record of taking ownership and driving resolution
Highly skilled verbal, written communication, and data presentation
Effective communication with both business and technical teams
Ability to take loosely defined business questions and translate them into clearly defined technical / data specifications
Passion for operational excellence with a commitment to delighting customers
French, German, Italian, Spanish or other European language skills would be advantageous but is not essential
Master’s degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
Experience with statistical and data science disciplines and technologies