• 2+ years of analyzing and interpreting data with Redshift, Oracle, No SQL etc. experience
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, Quick Sight, Micro Strategy, Power BI) and statistical methods (e.g. t-test, Chi-squared)
• Experience with scripting language (e.g., Python, Java, or R)

Job Description
Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for strategy planning, transportation and fulfillment network? If so, then this is the job for you.

Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in emerging countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

Key job responsibilities
1. Translating business questions and concerns into specific analytical questions that can be answered with available data using BI tools; produce the required data when it is not available.
2. Apply statistical and standard methods to specific business problems and data.
3. Create global standard metrics across regions and perform benchmark analysis.
4. Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
5. Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
6. Collaborate with colleagues from multidisciplinary data engineering and business backgrounds.
7. Develop efficient data querying and modeling infrastructure.
8. Utilizing code (Python, SQL, Tableau etc.) for analyzing data and building statistical models.
9. Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.

• Master's degree, or Advanced technical degree
• Knowledge of data modeling and data pipeline design
• Experience with statistical analysis, co-relation analysis