Job Description :
Amazon.com, Inc. is a US-based multinational electronic commerce company headquartered in Seattle, Washington. Jeff Bezos founded Amazon.com, Inc. in 1994 and launched it online in 1995. Amazon.com started as an online bookstore, but soon diversified, selling DVDs, CDs, MP3 downloads, computer software, video games, electronics, apparel, furniture, food, and toys. Today, as a market leader in online retail, Amazon product lines include Amazon.com, A9.com, IMDb, Kindle, Amazon Web Services, Alexa.com, Audible.com, A2Z Development, Alexa Internet and Endless.com.
Global Catalog Operations
High quality data is the foundation of building awesome user experiences. It powers unrivaled product discovery, informs customer buying decisions, offers a large selection and positions Amazon as the first stop for product discovery. The quality of Amazon’s product catalog is one of the most significant controllable inputs into building great customer experiences. Now take the world’s largest product catalog and imagine how you could influence the experience for millions of customers on the world’s largest e-commerce site. Amazon’s Catalog Quality group own catalog quality. We combine customer behavior and expert knowledge to identify pathologies, define quality standards, and measure the state of the catalog. We build scalable solutions which improve both the buying and selling experiences at Amazon.
About you
Amazon’s Global Catalog Operations team is looking for a customer focused Business Analyst to help us make the world’s best product catalog even better. The successful candidate should be able to leverage the latest in data mining, predictive modeling and business analysis to discover key meaningful, actionable insights to improve our catalog quality. You have outstanding quantitative and data analysis skills, good business acumen, intense curiosity, superior communication skills, and the ability to use data and models to influence cross-functional teams. You have a strong bias toward data driven decision making, and an innate ability to understand how metrics relate to business problems and to each other. You are experienced with and excited by mining multiple large and complex datasets in order to deep dive and understand the root causes of problems and make recommendations.
Roles and Responsibilities
In this role, the Business Analyst will be responsible for leveraging data driven approach to proactively identify and quantify opportunities to improve the quality of Amazon’s catalog in order deliver outstanding experience to our customers. Here are some key responsibilities of the role:
. Partner with technology leaders, program managers, operations leaders and other internal stakeholders globally to identify, quantify and solve for opportunities to improve Catalog Quality.
.
. Define, measure and present metrics / reports on different programs to Senior Level Management. Design new metrics and enhance existing metrics to support the future state of business processes and ensure sustainability.
.
. Learn and understand a broad range of Amazon’s data resources and know how, when, and which to use
.
. Helping operations with regular and ad hoc query/ data ETL jobs and work on simplifying/ standardizing operational metrics and reporting
.
. Enable effective decision making by retrieving, aggregating and synthesizing massive data from multiple sources and compiling it into a digestible and actionable format. Develop solutions that utilize the highest standards of analytical rigor and data integrity. Write high quality code to retrieve and analyze data. Drive insights and action we can take to improve the customer experience
.
. Analyze and solve business problems with focus on understanding root causes and driving forward-looking opportunities
.
. Perform statistical tests to establish trends, patterns, seasonality. Use data mining, model building, and other analytical techniques to develop predictive models
.
. Propose optimal techniques to sample the massive product catalog for humans to audit different dimensions of data quality issues
.
. Establish relationship between output metric and its drivers in order to identify critical drivers and control the critical drivers so as to achieve the desired value of output metric.
.
. Ability to write functional specs for tools and drive UAT based on business requirements
. Communicate complex analysis, insights and recommendations to stakeholders and business leaders, both verbally and in writing
.
Basic Qualifications :
. 1+ years of experience in financial/business analysis
. Experience with SQL or ETL
. Experience defining requirements and using data and metrics to draw business insights
. Bachelor’s degree in Business, Computer Science, Computer Information Systems, Engineering, Operations Research, Mathematics, Statistics or other business/analytical disciplines.
. 2+ years of professional experience in analytics, business analysis or comparable consumer analytics position using databases in a business environment with large-scale complex datasets.
. Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause analyses
. Advanced working knowledge of data mining using SQL, ETL, data warehouse as well as Excel in a business environment with large-scale, complex datasets.
. Proven ability to independently frame business problems and come up with quantitative analysis to inform decisions ability to boil down big data into key business insights.
. Ability to deal with ambiguity and competing objectives in a fast paced environment
. Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams.
Preferred Qualifications :
. Master’s degree in Business, Computer Science, Computer Information Systems, Engineering, Operations Research, Mathematics, or other business/analytical disciplines.
. 2+ years of professional experience in analytics, business analysis, or comparable consumer analytics position using databases in a business environment with large-scale complex datasets


Source link