Applied Scientist II, Amazon Recommerce India
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Science · Data Analysis
In short
Amazon Recommerce India is seeking an Applied Scientist II to develop and adapt machine learning models for predicting return salability, detecting defects with computer vision, and optimizing disposition and pricing. This role involves end-to-end ownership from problem framing to production deployment, partnering with engineering, product, and operations teams.
Responsibilities
- Build ML models for automated returns grading to predict salability with minimal human touch.
- Develop computer-vision models for defect detection, condition assessment, and anomaly/fraud identification.
- Build disposition-prediction and routing models to direct units to their highest-value recovery path.
- Develop pricing and recovery-optimization models for dynamic, grade- and condition-aware pricing.
- Adapt Worldwide ML models to India's data, catalog, languages, and operational constraints.
- Own the full model lifecycle: problem framing, data pipelines, feature engineering, training, evaluation, monitoring, and retraining.
- Partner with engineering, product, and operations teams.
- Use modern GenAI/LLM tooling to accelerate research and delivery.
Requirements
- 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 algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
Desired Qualifications
- Experience using Unix/Linux.
- Experience in professional software development.
#Applied Scientist#Recommerce#Machine Learning#Computer Vision#Data Science#India#Bengaluru
Company
Amazon
Job Posted
4 weeks ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Mid-Senior
Locations
Bengaluru, India
Qualification
Master, Doctoral
Applicants
Be an early applicant