Job Description

• Bachelor's degree in Computer Science, Mathematics, Statistics, Operations Research.
• Experience in solving business problems by leveraging advanced analytical techniques such as predictive modelling (linear regression, time series forecasting), classification algorithms (K-means, KNN, SVM etc.)
• Proficiency in SQL and in one or more programming language - Python, Scala, Ruby and Java.
• Knowledge of data management fundamentals, data storage principles, ETL, Data Modeling, and Data Architecture.
• Knowledge on using business intelligence reporting tools - Tableau/QuickSight/Looker.
• Familiar with theory and practice of information retrieval, relevance, Statistics, and data mining and skilled at data visualization and presentation.
• Excellent problem solving skills, combined with the ability to present your findings/insights clearly and compellingly in both verbal and written form.


At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. Over 2 million Sellers in 10 countries ship billions of products for sale on the Amazon Marketplace. To meet our sellers' needs, we are constantly innovating and building on new ideas. Fulfillment by Amazon (FBA) Inbound analytics and data science team partners with product team to optimize inbound supply chain by influencing right tradeoffs among cost, speed and network capacity utilization.



FBA Product Analytics team is looking for an individual with excellent analysis and statistical skills, deep knowledge of business intelligence solutions, and the ability to work with product development, and business teams. The successful candidate will have passion for data and analytics, be a self-starter comfortable with ambiguity, with strong attention to detail.



Key job responsibilities



Major responsibilities

• Develop business metrics and analysis to inform product strategy and influence key strategic initiatives.
• Develop clear communications for recommended actions.
• Establish self-service automated reporting processes for tracking and diving deep into the data.
• Partner with data engineers to establish new data pipelines and document logic for business metrics.
• Use machine learning and statistical techniques to infer impact of product and policy decisions on business outcomes.


A day in the life

As a Business Intelligence Engineer, you will help develop an analytic solution to drive deep dives, provide insights into the health and state of the Operations and measure business impact. You will transform data into actionable business information, and will make it readily accessible to stakeholders worldwide. You will own the design, creation, and management of extremely large datasets. From Day 1, you will be challenged with a variety of tasks, ranging from creating datasets, reports, dashboards to metadata modeling, pipeline monitoring. You will interact with internal program and product owners, and technical teams to gather requirements, structure scalable and perform data solutions, and gain a deep understanding of key datasets. You will design, implement and drive adoption of new analytic technologies and solutions and promote industry standard best practices. You will be responsible to tune query performance against large and complex data sets. You will help translate analytic insights into concrete, actionable recommendations for business or product improvement.



About the team



Our benefits include:

• Work on high-impact, high-visibility projects that drive the experience for millions of customers.
• The opportunity to use and learn state-of-the-art data management solutions.
• Excellent opportunities, and ample support, for career growth, development, and mentor-ship.
• Competitive compensation, including relocation support.
• 5+ years of experience as a Business/Financial Analyst, BI Engineer or Systems Analyst preferably in an internet-based company with large, complex data sources.
• Experience conducting large scale data analysis to support business decision making.
• Experience developing insights across various areas of customer-related data: financial, product, and marketing.
• Ability to deal with ambiguity and competing objectives in a fast paced environment.
• Proven problem solving skills, attention to detail, and exceptional organizational skills
• Track record of strong interpersonal and communication (verbal and written) skills. Must be able to explain technical concepts and analysis implications clearly to a wide audience, including senior executives, and be able to translate business objectives into actionable analyses and contribute to documents
• Familiarity with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Knowledge of scripting for automation (e.g. Python, Perl, Ruby)