Business Intelligence Engineer
Merch by Amazon is a rapidly expanding Amazon business that provides a make-on-demand service for creating, publishing, promoting, and selling graphic merchandise such as t-shirts, hoodies, PopSockets, and more. Content creators upload designs and we list, sell, print, and ship these items to Amazon customers. Our customers get great graphic products, content creators get a generous royalty.
Our Data Science team is looking for a talented, creative, and passionate Business Intelligence Engineer to own and lead business analysis, insights, and reporting for Merch by Amazon. Data analysis is at the core of Amazon’s culture, and your work will have a direct impact on decision making and strategy for our team. You will be gathering customer insights, mining data, making recommendations, and most importantly “teaching to fish” by working with subject matter experts and business leaders to think analytically and use data in key business decisions.
This position will report to the Sr. Manager of Applied Science and work alongside Scientists and Engineers to leverage data to benefit our designers, brands, and customers. This role requires a customer obsessed individual with excellent statistical and analytical abilities, deep knowledge of data analysis and reporting solutions, and an outstanding business acumen. You are a self-starter comfortable with ambiguity, possess a strong attention to detail, and show an ability to work in a fast-paced and entrepreneurial environment. You have a strong bias towards data-driven decision making, and are excited by the prospect of collaborating with internal and external teams to define and implement solutions that will yield benefits to Amazon customers around the world.
- Foster and expand the analytical culture in Merch by Amazon by building self-service solutions and teaching business leaders and subject matter experts to use data better and be self sufficient in their reports and analyses.
- Own the design, development, and maintenance of high impact shared reports, analyses, and dashboards to provide visibility into how well the business is serving our customers, content creators, and brands.
- Apply data mining, quantitative analysis, and statistical models to understand how our customers interact with us and identify ways to improve the customer experience.
- Conduct written and verbal presentations to share insights and recommendations to audiences of varying levels of technical sophistication.
Merch by Amazon - it's not just a job, it's a wardrobe. If you're looking for a chance to build data-driven products with a team of top-notch engineers and scientists, for a new business that promises to shake things up on behalf of all sorts of customers; if you're an expert analyst with a gritty, start-up mentality, and want to build quick, learn from data, and level-up those around you in their data skills; if you wear t-shirts, or at least appreciate customers who do - well we might have a job for you.
- Bachelors degree in a quantitative field such as business, economics, engineering, mathematics, statistics or data science
- 2+ years hands on analytics work experience with proven quantitative orientation.
- Excellent working knowledge of large data manipulation and analysis using complex SQL
- Advanced Excel skills, including arrays, pivot tables, and nested formulas
- Experience in designing and delivering cross functional custom reporting solutions
- Experience communicating analytical outcomes through written communication to both business and technical teams.
- Advanced degree in business (MBA), math, statistics, engineering, computer science or related discipline
- Demonstrated ability to coordinate projects across functional teams, including engineering, IT, product management, marketing, finance, and operations
- Experience with data visualization using Tableau, Re:dash, Quicksight, or similar tools
- Experience with Python, R, or other statistics/machine learning software
- Knowledge of scripting for automation (Linux shell scripts, Python, etc)
- High-level knowledge of various machine learning techniques and key parameters that affect their performance
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.