Data Scientist Internship at Amazon – AI/ML & Predictive Analytics | Bangalore, Hyderabad, Chennai

Job Description:

Amazon is seeking highly motivated Data Scientist Interns with strong analytical, problem-solving, and leadership skills. This internship provides a unique opportunity to work on complex, data-driven problems that impact millions of customers. You’ll work closely with cross-functional teams to build predictive models and data pipelines that drive business insights and improve customer experience.

Location: Bangalore, Hyderabad, Chennai
Internship Type: Full-time | On-site
Commitment: Full-time availability during internship (no parallel academic or work commitments allowed).

Job Description :-

Company:	Amazon
Job Role:	Data Scientist Intern
Batches:	Recent Batch
Degree:	Bachelor’s/Master’s Degree
Experience:	Freshers
Location:	Hyderabad/Chennai/Delhi, INDIA
CTC/Salary:	INR 5-6.5 LPA (Expected)

Key Responsibilities:

• Apply data analysis and statistical modeling to improve customer experience and influence data-driven decisions
• Identify key predictors and trends affecting business operations and build forecasting models
• Translate complex datasets into actionable insights and recommendations through analytical reporting
• Lead and collaborate with cross-functional teams to implement high-impact data science solutions
• Solve business problems at the root level using structured and unstructured data sources
• Present findings and strategies through clear, data-driven business recommendations.

Basic Eligibility:

• Must be 18 years of age or older
• Must be available for full-time internship without academic or employment conflicts during the internship duration

Preferred Qualifications:

• Hands-on experience in R, SAS, MATLAB, or SQL
• Skilled in data transformation, feature engineering, model selection, training, and validation
• Familiarity with machine learning and deep learning frameworks like TensorFlow, PyTorch, Caffe, or MXNet
• Exposure to big data platforms such as Apache Spark and Hadoop
• Strong background in Computer Science, Engineering, Operations Research, or Process Control
• Knowledge of automation, optimization, and model deployment at scale is a plus.

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