The Trustworthy Shopping Experience team is looking for a Business Intelligence Engineer to help us protect our customers from defective, dangerous products and guarantee them a worry-free shopping experience. Are you a self-starter who is comfortable handling complex data sets and working through ambiguity? If so, this role is for you!
Key job responsibilities
As a Business Intelligence Engineer in the Trustworthy Shopping Experience team, you will support our goal to be the most customer-centric company on Earth. To get there, we need exceptionally talented, bright and driven people.
In this role you will use your passion for data to generate actionable insights through the development of metrics, dashboards and deep dive analyses. You will track existing and emerging abuse vectors, generate actionable insights, define and implement new initiatives, and quantify our progress using metrics. You dive into the details of the business metrics and provide insight within the team to assess, prevent, and predict e-commerce risk. You will collaborate with partner teams to define metrics to measure the success of our processes and initiatives, develop scalable reporting solutions, and provide objective and tangible data that allows the team to identify improvement areas, make informed decisions, and monitor efficiency of our policies and strategies. You will do this in partnership with other Amazon teams including program, product, and partner data teams across the world, hence cross-team coordination and collaboration skills are essential.
A day in the life
You track and publish our business metrics, partner with the internal program teams to identify root-causes of spikes or plummets in key metrics while carrying on mid-term to long-term projects to improve our policies, processes and tools and communicating with data science/engineering teams.
About the team
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching tens of thousands at chapters across the globe. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Harmony
Our team puts a high value on work-life harmony. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We encourage and empower you to find your own balance between your work and personal lives.
BASIC QUALIFICATIONS
1. Degree in Computer Science, Mathematics, Statistics, Finance, or related field
2. Knowledge of at least one programming language (Python, R, Java, C++, Haskell or similar)
3. Experience in Microsoft Excel and querying data sets using SQL
4. Fluency in written and spoken English
PREFERRED QUALIFICATIONS
1. Team player with the ability to collaborate in a diverse team including other geographic locations and cultures
2. Effective verbal and written communication skills
3. Advanced Degree in Computer Science, Mathematics, Statistics, Finance, or related field
4. Practical experience in data analysis such as data warehousing, regression modelling, forecasting, data mining
5. Familiarity with AWS services such as S3, Redshift, EMR, Athena, etc.
6. Experience with Machine Learning
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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