Data Scientist III, Rapid & Rural Logistics (R2L) Science & AI
Amazon is hiring a Data Scientist III, Rapid & Rural Logistics (R2L) Science & AI in Bellevue, United States. It pays $175k-$237k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
- Pay on this posting starts in line with the typical data scientist posting on Level.
- The posting mentions machine learning, data science and causal inference among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Develop machine learning models and data science solutions for ultra-fast logistics and grocery supply chains.
R2L Science & AI team sits under R2L and is a central team for all Data Science/AI related asks. We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team.
Key job responsibilities
We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team. This position is critical in helping us learn more about our data and finding opportunities to delight customers with data driven insights and machine learning models. The Data Science and Analytics team owns data science, data engineering, and business intelligence. You will be supporting multiple business and technical stakeholders with high velocity analytics.
This role is uniquely positioned in the team as we have a growing need for looking around corners, prioritizing opportunities using data driven insights, and finding solutions to these opportunities using different machine learning techniques and causal inference models.
You will be diving deep in our data and have a strong bias for action to quickly produce high quality data analyses with clear findings and recommendations. As part of our journey to learn about our data, some opportunities may be a dead end and you will be balancing unknowns with delivering results for our customers.
A day in the life
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
Learn more about our benefits here: https://amazon.jobs/en/internal/benefits/us-benefits-and-stock
Basic qualifications
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
Preferred qualifications
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 175,100.00 - 236,900.00 USD annually
USA, WA, Bellevue - 159,200.00 - 215,300.00 USD annually
How we rate this
Data Scientist III, Rapid & Rural Logistics (R2L) Science & AI at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $175k
- Typical data scientist job
- $168k
This posting starts close to the typical data scientist job. See data scientist jobs
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where causal inference was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Machine learning, Data Science, Causal Inference, and Data Engineering. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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