Applied Scientist II, ROW AOP
3 weeks ago
We are looking for an Applied Scientist to join our growing Science Team. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. You will be responsible for building ML models to solve complex business problems and test them in production environment. The scope of role includes defining the charter for the project and proposing solutions which align with org's priorities and production constraints but still create impact. You will achieve this by leveraging strong leadership and communication skills, data science skills and by acquiring domain knowledge pertaining to the delivery operations systems. You will provide ML thought leadership to technical and business leaders, and possess ability to think strategically about business, product, and technical challenges. You will also be expected to contribute to the science community by participating in science reviews and publishing in internal or external ML conferences.
Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis:
• Using live package and truck signals to adjust truck capacities in real-time
• HOTW models for Last Mile Channel Allocation
• Using LLMs to automate analytical processes and insight generation
• Ops research to optimize middle mile truck routes
• Working with global science teams to affect pricing models and Shipments Per Route for $MM savings
• Deep Learning models to synthesize attributes of addresses
• Abuse detection models to reduce network losses
Key job responsibilities
1. Use machine learning and analytical techniques to create scalable solutions for business problems
Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes
2. Design, develop, evaluate and deploy, innovative and highly scalable ML models
3. Work closely with other science and engineering teams to drive real-time model implementations
4. Work closely with Ops/Product partners to identify problems and propose machine learning solutions
5. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
6. Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
7. Leading projects and mentoring other scientists, engineers in the use of ML techniques
As part of our team, candidate in this role will work in close collaboration with other applied scientists and cross functional teams on high visibility projects with direct exposure to the senior leadership team on regular basis.
About the team
This team owns all science initiatives of ROW (Rest of World, >10 countries) operations of Amazon spread across applied sciences, ops research, AI and so on.- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in solving business problems through machine learning, data mining and statistical algorithms- Experience using Unix/Linux
- Experience in professional software development
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
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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