Description
Amazon Robotics
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun.
Our Team
The Amazon Robotics Data Science, Business Intelligence & Data Engineering team discovers insights in vast and varied robotic data to help our engineering teams understand how their technologies operate across Amazon’s network of warehouses. We collaborate with designers, software and hardware engineers, and operations teams to understand product requirements, make feature trade-offs, design, and operate new applications of Amazon Robotics technology. We conduct relevant, insightful analysis and communicate the results through white papers and presentations. Our methods include design of experiments, statistical modeling, machine learning, financial analysis, and data visualization.
What You Will Do
You will work cross-functionally with engineering teams, program managers, and leaders throughout the organization to deliver projects aimed at characterizing and improving the performance of new robotic automation technology in Amazon's network of warehouses. In this role, you will use a combination of unified and disparate data sources to uncover insights delivered through decision-driving analytics white-papers and automated data visualizations to influence the development and deployment of cutting edge robotic technology. You will collaborate with Data Scientists, Data Engineers, and Program Managers to define and deliver world class analytics tools and insights to shape the robotic technology landscape.
What We Are Looking For
A jack-of-all-trades data professional with a passion for delivering insightful and influential solutions to challenging and ambiguous problems. A practiced analyst, who uses data engineering, statistics, data visualization, and data science to influence decision making in cross-functional teams. We are seeking an individual who can think holistically through compound problems to understand how systems work together to define and execute projects which drive improvements to robotic architecture or design.
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 87,000 employees across hundreds of chapters around the world. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust.
Flexibility
It isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
We care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
Basic Qualifications
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
3+ 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
Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
3+ years of relevant experience in areas such as data analytics, data science, data modeling, and statistical analysis and modeling
Preferred Qualifications
Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
Experience with forecasting and statistical analysis
Knowledge in building advanced visualizations in Tableau
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $79,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.