Sr Applied Scientist, Amazon Recommerce India

About this role

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Skills you'll use

What you'll do

• Build ML models for automated returns grading — predicting the salability of returned units from structured and unstructured signals so units can be evaluated with zero or minimal human touch, improving speed, accuracy, and recovery value.
• Develop computer-vision models for defect detection, condition assessment, and anomaly/fraud identification (including inside sealed packaging), and for establishing chain-of-custody and damage attribution across the returns journey.
• Build disposition-prediction and routing models that direct each unit to its highest-value recovery path (resale, repair, liquidation, donation, recycle) as early as possible in the network.
• Develop pricing and recovery-optimization models for liquidation and resale, moving from flat rates toward dynamic, grade- and condition-aware pricing.
• Adapt Worldwide ML models to India — retraining, recalibrating, and re-evaluating for India's return distribution, catalog, languages, and operational constraints, and closing the gaps that prevent a direct lift-and-shift.
• Own the full model lifecycle — problem framing, data pipelines, feature engineering, training, offline/online evaluation, monitoring, and retraining — with rigorous attention to calibration, drift, and business-metric impact.
• Partner cross-functionally with engineering (to productionize), product (to frame problems and measure impact), and operations (to ground models in how the network actually runs), and use modern GenAI/LLM tooling to accelerate research and delivery.
• A day in the life
• You start by reviewing the performance of a grading model in production — checking calibration and drift against last week's returns, and confirming the recovery-value lift is holding. Mid-morning, you dig into a computer-vision problem: improving detection of a damage type that's driving write-offs, using images captured across the returns journey. In the afternoon you work with a Worldwide science team to bring one of their models to India — scoping what retraining and recalibration India's data requires — then pair with an engineer to move your latest model toward production behind a clean evaluation gate. You close by framing a new problem with a product partner: quantifying the opportunity, defining the label and success metric, and sketching the modeling approach.

Who can apply

• - 6+ years of building machine learning models for business application experience
• - PhD, or Master's degree
• - Experience programming in Java, C++, Python or related language
• - Experience with neural deep learning methods and machine learning

About Amazon

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