Research Scientist II, Last Mile Science

AI in this role

tensorflowscikit-learn

Are you passionate about solving complex logistics challenges? Our Analytics team is at the forefront of enhancing delivery experiences through data-driven solutions and innovative technology. As a Research Scientist, you will join a team dedicated to optimizing our delivery network, ensuring reliable and efficient service to our customers. We are seeking an enthusiastic, customer-centric professional with strong analytical capabilities to drive impactful projects, implement advanced solutions, and develop scalable processes.
In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of our delivery operations. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity.
This role offers the opportunity to make a significant impact on our advanced logistics network while working with pioneering technology and data science applications.
Basic qualifications
• 3+ years of building machine learning models for business application experience
• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred qualifications:
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• 3+ years of extensive relevant research experience
• Deep expertise in Machine Learning
• Proficiency in programming
• Core competency in mathematics and statistics
• Track record of successful projects in algorithm design and product development
• Publications at peer-reviewed conferences or journals
• Strategic thinker with good execution skills
• Exhibits excellent business judgment
• Effective verbal and written communication skills
• Experience working with real-world data sets and building scalable models from big data
• Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow
• Experience with large scale distributed systems

Basic qualifications

- PhD, or Master's degree
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- 3+ years of building machine learning models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred qualifications

- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 3+ years of applied research experience
- Knowledge of deep learning, machine learning and statistics
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Knowledge of mathematical/statistical/physics fundamentals
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Track record of successful projects in algorithm design and product development.
- prior experience with mentorship and/or management of scientists
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business
- Effective verbal and written communication skills
- Experience working with real-world data sets and building scalable models from big data.
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow,
- Experience with large scale distributed systems

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.

How we score this

Research Scientist II, Last Mile Science at Amazon scores 88 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

TensorFlowscikit-learn

Questions you could be asked

What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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List these exact terms on your resume: TensorFlow and scikit-learn. 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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