Applied Scientist II, Seller Fee Science

Amazon; Bengaluru; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

Amazon is seeking an applied scientist to apply machine learning and AI to predict and reconcile product fee measurements globally. The role blends statistical modeling, NLP, image processing, and optimization, partnering with engineers to take solutions from research to production.

You will work with world-class economists, physicists, mathematicians, and computer scientists on problems requiring theoretical rigor and real-world impact, shaping fee systems used by millions of sellers.

Qualifications

• 3+ years of building models for business applications.
• PhD or Master’s in CS/CE/ML or related field with 4+ years experience.
• Proficiency in Java, C++, Python or related languages.
• Experience in algorithms, data structures, numerical optimization, data mining, parallel/distributed computing, HPC.
• Experience with state-of-the-art DL architectures, training/optimization, and pruning.

Responsibilities

• Identify opportunities to translate business challenges into well-defined scientific problems.
• Design, develop, and deploy AI/ML models to improve fee accuracy and policy-to-code translation.
• Partner with engineering/product teams to productionize solutions respecting latency and scalability.
• Apply experimentation, causal inference, and simulation to validate models at scale.
• Communicate innovations and results to cross-functional stakeholders; publish talks and artifacts.

Skills

3+ years experience

Algorithms & data structures

Numerical optimization

Data mining

Parallel & distributed computing

High-performance computing

Deep learning design

Model pruning

Education

PhD or Master’s in CS/CE/ML

Tools

Java

C++

Python

Job description

Description

Amazon’s third-party marketplace is a multibillion-dollar global ecosystem, connecting customers and sellers across the world through millions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improves the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence.

Description

Amazon’s third-party marketplace is a multibillion-dollar global ecosystem, connecting customers and sellers across the world through millions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improves the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence.

Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. For example, precision measurement of difficult to measure products, large-scale simulation of sales, inventory, and policy changes, as well as leveraging natural language understanding and automated reasoning to interpret policy, generate code, resolve disputes, audit fees, and respond to sellers at meaninful scale.

As an applied scientist on our team, this role will focus on the application of machine learning and artificial intelligence to predict and reconcile measurement of products globally. This blends together statistical modeling, application of NLP, image processing, classical machine learning, cost-benefit analysis, causal modeling, and optimization. Your work will shape not only how fees are implemented, but how they are interpreted, experienced, and trusted at scale. You will partner closely with engineers and product partners to take your solutions from research to production.

We are seeking scientists who are motivated by first principles, disciplined experimentation, and the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where mathematical rigor meets real-world complexity, and where your models, algorithms, and systems will directly influence the experience of millions of sellers. If you are driven to build elegant solutions to hard problems—and to see them operate in production at meaningful scale we would welcome the opportunity to build with you.

Key job responsibilities

• Identify opportunities to improve Seller Experience and translate ambiguous business challenges into well-defined scientific problems with measurable impact.
• Design, develop, and deploy AI/ML models that improve fee accuracy, automate policy-to-code translation, and enhance seller understanding of fee calculations.
• Partner closely with engineering and product teams to productionize solutions, meeting latency, scalability, reliability, and other system constraints.
• Apply rigorous experimentation, causal inference, and simulation methods to validate models and quantify business impact at scale.
• Communicate scientific innovations and results clearly to cross-functional stakeholders and contribute to the broader internal and external scientific community through publications, talks, and technical artifacts.

Basic Qualifications

• 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 state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Preferred Qualifications

• Experience applying theoretical models in an applied environment
• Experience building machine learning models or developing algorithms for business application
• Experience in designing experiments and statistical analysis of results
• 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.

Company - ADCI - BLR 14 SEZ

Job ID: A10371573