Business Analyst, AST Analytics
Job Description :
Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a highly respected e-commerce platform. As an extension of this, Amazon encourages sellers/vendors to offer products to Amazon customers through various advertising. The Advertiser Success team is a support function to the local sales and account management teams and helps provide scale to add new participants and help them engage effectively with the ad programs. We work on various ad programs covering NA, EU and APAC markets and we provide 24/7 coverage for operations.
Advertiser Success team (AST) is looking for a talented and driven Business Analyst who can extract meaning from large volumes of data to make the right business decisions. You will leverage your passion for BI to seek out and structure data to propel our reporting and analytics capabilities forward. You will work closely with senior leaders to understand their information needs and then build scalable solutions to deliver the key metrics to make business decisions.
Key job responsibilities
Reporting of key insight trends, using statistical rigor to simplify and inform the larger team of noteworthy story lines
Respond with urgency to high priority requests from senior business leaders
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
Ensure data accuracy by validating data for new and existing tools. Learn and understand a broad range of Amazon's data resources and know how, when, and which to use and which not to use
A day in the life
You will work in one of the complex data environments and will innovate on behalf of our advertising customers. You will bring data together to answer business questions and guide our businesses by pushing the boundaries of data analytics and science to solve analytics problems in a fast-moving environment. You will collaborate with internal partners from tech, science, sales, marketing, and other cross-functional teams to deliver successfully against high organizational standards.
About the team
Advertiser Success Analytics team own roadmap for advanced analytics and insights across search and display advertising products and help drive success for advertisers. Advertiser success is core to Amazon's growth, as it helps drive awareness, consideration, and purchase of their products by hundreds of millions of consumers around the world, and generates revenue which helps us lower prices and invest in improvements to our customer experience. We are a highly motivated, collaborative and fun-loving team with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
Basic Qualifications :
Bachelor's degree in Business, Economics, Finance, Engineering, Statistics, Computer Science, Mathematics or related field, or equivalent experience
3+ years of relevant work experience in a business analyst/data analyst/statistical analysis role
Experience in developing requirements and formulating business metrics for reporting
Advanced SQL skills and experience in joining/cleansing datasets from multiple sources
Advanced Microsoft Office skills, particularly Excel and analytical platforms
Strong active listener with solid written and verbal communication skills
Ability to work cross-functionally, building and maintaining trust with internal stakeholders
Preferred Qualifications :
Experience leading and coordinating broad business reviews
Ability to display complex quantitative data in a simple, intuitive format and to present findings in a clear and concise manner
Experience with scripting languages such as Python or R
Familiarity with data visualization tools, e.g. Tableau, QlikView, QuickSight
Experience with statistical analysis, regression modeling and forecasting, time series analysis, data mining, financial analysis, dynamic pricing, demand modeling, game theory and customer/product segmentation