Data Scientist, Vehicle Engineering, Testing, Reliability

- 3+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
- Simulation tools and methods
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company

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.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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.
Vehicles Programs & Engineering within Amazon’s Last Mile organization is looking for a Data Scientist to leverage Amazon’s vast amount of data to answer business critical questions on how best to maintain, utilize and operate our fleet of tens of thousands of vehicles.
The Vehicle Programs and Engineering team works on Amazon's last-mile vehicle initiatives. The key partners to this team will include (but not be limited to) Finance, Analytics Team, Maintenance, Fleet Ops, Safety and Global teams. As a scientist on our team, you will develop and lead new technical solutions, influence business critical decision-making with massive scale, and influence multiple organizations and geographies.
To be successful in this role, you'll need to wrangle messy data from internal and external sources, manage stakeholder priorities, and communicate technical concepts to both technical and non-technical audiences. You'll work on unique problem spaces to improve our fleet at a scale unmatched in industry and be able to see the impact of your work across organizations.


Key job responsibilities
- Provide strategic and tactical advice based on data insights to multiple business teams.
- Build prototype and production intent forecasting and decision models
- Engineer new solutions to analyze and interpret a variety of data sources (internal and 3rd party)
- Leverage business acumen and technical expertise to create new performance metrics, uncover trends, and highlight root causes of issues
- Manage multiple projects simultaneously
- Work with product, technology, and analytics stakeholders to support organization wide goals
- Communicate findings with senior leadership
- Learn, explore, apply, and gain expertise in many internal Amazon data and public AWS products such as Glue, Redshift, Quicksight, and Lambda