Amazon

GO-AI ACES Business Analyst, GO-AI

Job Description

The candidate is expected to
a) be very analytical and be able to justify decisions and approaches with data.
b) be able to deal with a high degree of ambiguity
c) be able to take a complex problem and break it down to smaller digestible chunks
d) be able to define a logical and step by step approach to achieving a lofty goal
e) be comfortable with processes and process design/analysis
f) have the ability to influence without authority and do so by using data and facts
g) be able to deal with varied stakeholders and earn their trust.
h) have a good understanding of Macro and SQL with hands on experience

Key job responsibilities
Roles and Responsibilities:

· Identify, plan and execute automation projects within the team.
· Create and work on big data using SQL, Amazon S3, Quick sight to provide actionable insights
· Support the business growth in constrained environments with frugal and innovative solutions
· Make the existing processes scalable by identifying and implementing available tools/automation
· Create ETLs, dashboard and optimised SQL queries
· Utilize exceptional problem-solving and communication skills to influence business, operations and technical audiences

About the team
The Global Operations – Artificial Intelligence (GO-AI) team is an initiative, which remotely handles exceptions in the Amazon Robotic Fulfillment Centers Globally. GO-AI seeks to complement automated vision based decision-making technologies by providing remote human support for the subset of tasks which require higher cognitive ability and cannot be processed through automated decision making with high confidence. This team provides end-to-end solutions through inbuilt competencies of Operations and strong central specialized teams to deliver programs at Amazon scale.- 1+ years of data analytics or automation experience
- 1+ years of capacity planning, operations planning, business analysis or similar experience
- Bachelor's degree
- Knowledge of data pipelining and extraction using SQL
- Knowledge of SQL and Excel at a moderate or advanced level
- Experience with data mining tools like SQL, SAS, SPSS, or similar


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