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Amazon Transportation team is looking for an innovative, hands-on and customer-centric Business Analyst for Analytics team. Candidate must be detail oriented, have superior verbal and written communication skills, organizational skills, excellent technical skills and should be able to juggle multiple tasks at once.
Candidate must be able to identify problems before they happen and implement solutions that detect and prevent outages. The candidate must be able to accurately prioritize projects, make sound judgments, work to improve the customer experience and get the right things done.
This job requires you to constantly hit the ground running and have the ability to learn quickly. Primary responsibilities include defining the problem and building analytical frameworks to help the operations to streamline the process, identifying gaps in the existing process by analyzing data and liaising with relevant team(s) to plug it and analyzing data and metrics and sharing update with the internal teams.
Key job responsibilities
- Apply multi-domain/process expertise in day to day activities and own end to end roadmap.
- Translate complex or ambiguous business problem statements into analysis requirements and maintain high bar throughout the execution.
- Define analytical approach; review and vet analytical approach with stakeholders.
- Proactively and independently work with stakeholders to construct use cases and associated standardized outputs
- Scale data processes and reports; write queries that clients can update themselves; lead work with data engineering for full-scale automation
- Have a working knowledge of the data available or needed by the wider business for more complex or comparative analysis
- 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) - When needed, pull data from multiple similar sources to triangulate on data fidelity
- Actively manage the timeline and deliverables of projects, focusing on interactions in the team
- Provide program communications to stakeholders
- Communicate roadblocks to stakeholders and propose solutions
- Represent team on medium-size analytical projects in own organization and effectively communicate across teams
A day in the life
- Solve ambiguous analyses with less well-defined inputs and outputs; drive to the heart of the problem and identify root causes
- Have the capability to handle large data sets in analysis through the use of additional tools
- Derive recommendations from analysis that significantly impact a department, create new processes, or change existing processes
- Understand the basics of test and control comparison; may provide insights through basic statistical measures such as hypothesis testing
- Identify and implement optimal communication mechanisms based on the data set and the stakeholders involved
- 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 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.
Basic Qualifications
- 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- 5+ years of doing one of several roles: quantitative/financial analysis, retail buying, retail planning & allocation, product/project management, pricing, marketing or e-commerce experience
Preferred Qualifications
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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