Senior Data Scientist, IES CFX & Prime

Amazon Inc.; Bengaluru; In loco; INR 4.000.000 - 7.000.000; Tempo pieno

Descrizione del lavoro

Amazon is seeking a senior data scientist to develop and deploy machine learning systems across millions of customer interactions, supporting the Amazon Fulfillment & Prime analytics team. The role emphasizes end-to-end ML lifecycle, scalable models, and collaboration across countries with travel to MX and BR.

The team focuses on cutting-edge ML methods, MLOps, and producing reports to drive customer experience improvements globally.

Competenze

• 8+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python) or statistical software.
• 8+ years of data scientist experience.
• Experience with statistical models such as multinomial logistic regression.

Mansioni

• End-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models.
• Strong foundation in machine learning and statistical modeling.
• Deploy ML solutions into production environments.
• Apply ML and statistical techniques to create scalable abuse-detection solutions for fraudulent customer behaviors.
• Innovate with GenAI to build automated solutions for customer promotions.
• Collaborate with cross-functional teams to develop scalable ML/statistical models for millions of customers across 10+ countries.
• Willing to travel to Mexico (MX) and Brazil (BR); coordinate with CET hours for overlap with teams.

Conoscenze

SQL

Python

Multinomial logistic regression

R

SAS

Matlab

Descrizione del lavoro

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?

If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide.

Key job responsibilities

• Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models.
• Strong foundation in machine learning and statistical modeling.
• Experience deploying ML solutions into a production environment.
• Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes.
• Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions.
• Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries.
• Willing to travel to Mexico (MX) and Brazil (BR).
• Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams.

About the team

You’ll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.

You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

Basic Qualifications

• 8+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 8+ years of data scientist experience
• Experience with statistical models e.g. multinomial logistic regression

Preferred Qualifications

• Experience as a leader and mentor on a data science team

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