Jobs
Benefits & Perks
•Healthcare
•401(k)
•Parental Leave
•Healthcare
•401k
•Parental Leave
Required Skills
SQL
Python
Java
R
Tableau
Quicksight
Data Analysis
Statistical Methods
Come help Amazon create cutting-edge data and science-driven technologies for delivering packages to the doorstep of our customers! The Last Mile Routing & Planning organization builds the software, algorithms and tools that make the “magic” of home delivery happen: our flow, sort, dispatch and routing intelligence systems are responsible for the billions of daily decisions needed to plan and execute safe, efficient and frustration-free routes for drivers around the world. Our team supports deliveries (and pickups!) for Amazon Logistics, Prime Now, Amazon Flex, Amazon Fresh, Lockers, and other new initiatives.
As part of the Last Mile Science & Technology organization, you’ll partner closely with Product Managers, Data Scientists, and Software Engineers to drive improvements in Amazon's Last Mile delivery network. You will leverage data and analytics to generate insights that accelerate the scale, efficiency, and quality of the routes we build for our drivers through our end-to-end last mile planning systems. You will present your analyses, plans, and recommendations to senior leadership and connect new ideas to drive change. Analytical ingenuity and leadership, business acumen, effective communication capabilities, and the ability to work effectively with cross-functional teams in a fast paced environment are critical skills for this role.
Responsibilities:
· Create actionable business insights through analytical and statistical rigor to answer business questions, drive business decisions, and develop recommendations to improve operations
· Collaborate with Product Managers, software engineering, data science, and data engineering partners to design and develop analytic capabilities
· Define and govern key business metrics, build automated dashboards and analytic self-service capabilities, and engineer data-driven processes that drive business value
Navigate ambiguity to develop analytic solutions and shape work for junior team members
Basic Qualifications
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL 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, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
Preferred Qualifications
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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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About Amazon

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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