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Amazon
Amazon 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 continues to grow and evolve as a world-class e-commerce platform. The AOP team is an integral part of this and strives to provide Analytical Capabilities to fulfil all customer processes in the IN-ECCF regions.
The Business intelligence engineer would support the analytical requirements of the IN-ECCF Operations Analytics team. Candidate will be responsible for conducting deep dive analyses to solve complex business problems. He/ she will also be responsible for creating robust/automated reporting frameworks to increase visibility into data and enable data driven decision making. Another key aspect of the job is to unearth insights from data to help the operations team in driving process excellence. This position requires excellent statistical knowledge, superior analytical abilities, good knowledge of business intelligence solutions and exposure to efficient data engineering practices. The BIE will also be a good stakeholder manager as he/she will have to work closely with Ops stakeholders. Candidate should be comfortable with ambiguity, capable of working in a fast-paced environment, continuously improving technical skills to meet business needs, possess strong attention to detail and be able to collaborate with customers to understand and transform business problems into requirements and deliverables.
Key job responsibilities
1) Apply multi-domain/process expertise in day to day activities and own end to end roadmap.
2) Translate complex or ambiguous business problem statements into analysis requirements and maintain high bar throughout the execution.
3) Define analytical approach; review and vet analytical approach with stakeholders.
4) Proactively and independently work with stakeholders to construct use cases and associated standardized outputs
5) Scale data processes and reports; write queries that clients can update themselves; lead work with data engineering for full-scale automation
6) Have a working knowledge of the data available or needed by the wider business for more complex or comparative analysis
7) Work with a variety of data sources and Pull data using efficient query development that
requires less post processing (e.g., Window functions, virt usage)
8) When needed, pull data from multiple similar sources to triangulate on data fidelity
9) Actively manage the timeline and deliverables of projects, focusing on interactions in the team
10) Provide program communications to stakeholders
11) Communicate roadblocks to stakeholders and propose solutions
12) Represent team on medium-size analytical projects in own organization and effectively communicate across teams
A day in the life
1) Solve ambiguous analyses with less well-defined inputs and outputs; drive to the heart of the problem and identify root causes
2) Have the capability to handle large data sets in analysis through the use of additional tools
3) Derive recommendations from analysis that significantly impact a department, create new processes, or change existing processes
4) Understand the basics of test and control comparison; may provide insights through basic statistical measures such as hypothesis testing
5) Identify and implement optimal communication mechanisms based on the data set and the stakeholders involved
6) Communicate complex analytical insights and business implications effectively
About the team
AOP (Analytics Operations and Programs) team is missioned to standardize BI and analytics capabilities, and reduce repeat analytics/reporting/BI workload for operations across IN, AU, BR, MX, SG, AE, EG, SA marketplace.
AOP is responsible to provide visibility on operations performance and implement programs to improve network efficiency and defect reduction. The team has a diverse mix of strong engineers, Analysts and Scientists who champion customer obsession.
We enable operations to make data-driven decisions through developing near real-time dashboards, self-serve dive-deep capabilities and building advanced analytics capabilities.
We identify and implement data-driven metric improvement programs in collaboration (co-owning) with Operations teams- 10+ years of professional or military experience
- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining
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