Data Scientist II, International Machine Learning

Amazon is hiring a Data Scientist II, International Machine Learning in Gurugram, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
Tools and skills the posting cites include Python, Machine learning and data science.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Design, develop, and deploy scalable machine learning models and solutions to optimize international consumer business operations.

PythonMachine learning

machine-learningdata-sciencestatistical-modelingbig-datapredictive-modeling

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for International Consumer Businesses.

Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions

We are developing state-of-the-art machine learning solutions to accelerate the Amazon growth story. Amazon is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the International Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML.

Key job responsibilities
- 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
- Design, develop, evaluate and deploy, innovative and highly scalable ML models
- Work closely with software engineering teams to drive real-time model implementations
- Work closely with business partners to identify problems and propose machine learning solutions
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
- Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
- Leading projects and mentoring other scientists, engineers in the use of ML techniques

About the team
International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

Basic qualifications

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
- Experience in Fintech, lending, or credit risk is highly preferred.
- Experience in developing ML model across credit lifecycle (Pre underwriting, underwriting, post underwriting, collections etc.)
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication

Preferred qualifications

- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in a ML or data scientist role with a large technology company
- Experience converting insights into strategy and communicating complex ideas clearly and logically in written communication
- 3+ years of experience in developing ML model across credit lifecycle (Eligibility, underwriting, collections etc.)
- 3+ years of experience in Fintech, lending, or credit risk

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.

How we rate this

Data Scientist II, International Machine Learning at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Scientist II, International Machine Learning is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN, HR, Gurugram.
The job was posted on August 26, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningData ScienceStatistical ModelingBig DataPredictive ModelingPython

Also common in data scientist jobs at this level

LLM Generative AI AWS Spark PyTorch Deep learning

Pay

Typical data scientist job: $168k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?
Tell me about a project where statistical modeling was part of your work. What did you do?
Tell me about a project where big data was part of your work. What did you do?
Tell me about a project where predictive modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Data Science, Statistical Modeling, Big Data, and Predictive Modeling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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