Are you a bright, motivated student passionate about leveraging data and advanced algorithms to solve real-world problems? Amazon is offering exciting internship opportunities for both Data Scientist Interns (Job ID: 2736671) and Applied Scientist Interns (Job ID: 2751860) across multiple locations in India (Bangalore, Chennai, Hyderabad, Delhi, Pune).
Whether your strength lies in statistical modeling for business decisions or developing cutting-edge ML/DL/NLP/CV algorithms, these full-time internships provide a unique chance to make a significant impact on Amazon’s consumer products and systems, guided by a pioneer engineering and research community. Prepare for a fast-paced, agile environment where your analytical skills and innovative thinking will thrive.
Overview | Amazon Internship Hiring 2025
| Company Name | Amazon |
| Job Role | Data & Applied Scientist Intern |
| Qualification | Bachelor’s, Master’s, or Ph.D. Degree |
| Experience | Fresher |
| Salary | INR Upto 8 LPA (Expected) |
| Location | Bangalore, Hyderabad, Chennai, Delhi |
Eligibility Criteria | Amazon Internship Hiring 2025
1) Academic Background: Currently enrolled in a Bachelor’s, Master’s, or Ph.D. Degree in Computer Science, Engineering, Operations Research, Process Control, or a related field at the time of application.
2) Programming Knowledge: Syntactical knowledge in programming languages such as Java, C/C++, Python, or Perl.
3) Commitment: Full-time commitment during the internship, with no conflicts including academic projects, classes, or other internships/employment.
4) Age: Must be 18 years of age or older.
5) Problem Solving: Excellent problem-solving skills and strong analytical abilities are essential.
Selection Process | Amazon Internship Hiring 2025
1) Application Submission: Submit your application online via the Amazon careers portal using the specific Job ID (2736671 for Data Scientist; 2751860 for Applied Scientist). Highlight your academic background, relevant skills, and programming proficiency.
2) Resume Screening: Amazon will review applications for academic qualifications, foundational computer science knowledge, programming experience, and any specific relevant experience (e.g., data analysis, ML research).
3) Technical Test / Interview: Expect rigorous assessments including online coding challenges and in-depth technical interviews. These will focus on data structures, algorithms, statistical concepts, ML fundamentals, and problem-solving relevant to the specific role.
4) HR Interview: This round will evaluate your communication skills, leadership potential, ability to handle ambiguous problems, learning agility, and cultural fit within Amazon’s fast-paced, customer-obsessed environment.
5) Document Verification & Offer Letter: If successful, your age and availability declaration (signed by a competent university authority) will be verified. Upon successful verification, you will receive an official offer letter for the internship.
6) Onboarding Process: Upon accepting the offer, you will go through the onboarding process. This includes completing necessary paperwork and orientation to integrate smoothly into the Amazon team at your assigned location (Bangalore, Hyderabad, Chennai, Delhi, or Pune).
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Roles & Responsibilities | Amazon Internship Hiring 2025
Data Scientist Intern: Roles & Responsibilities
1) Use data analyses and statistical techniques to develop solutions to improve customer experience and guide business decision-making.
2) Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations.
Applied Scientist Intern: Roles & Responsibilities
1) Bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings.
2) Develop state-of-the-art Machine Learning, Natural Language Processing, Deep Learning, and Computer Vision algorithms and designs using large data sets to solve real-world problems.
Skills & Competencies | Amazon Internship Hiring 2025
Data Scientist Intern: Skills & Competencies
1) Strong analytical rigor and experience in data analyses and statistical techniques.
2) Ability to identify predictors/causes of business problems and implement novel forecasting/prediction approaches.
Applied Scientist Intern: Skills & Competencies
1) Experience or research background in Machine Learning, Deep Learning, Natural Language Processing, or Computer Vision.
2) Proven analytical capabilities with strong knowledge of programming languages (C/C++, Python, Java, or Perl).
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How to Apply? | Amazon Internship Hiring 2025
- First, read through all of the job details on this page.
- Scroll down and press the Click Here button.
- To be redirected to the official website, click on the apply link.
- Fill in the details with the information provided.
- Before submitting the application, cross-check the information you’ve provided.
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Apply Link for Applied Scientist Intern : Link 1 & Link2
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General Interview Questions | Amazon Internship Hiring 2025
Interview Questions: Data Scientist Intern
1) Tell me about a time you made a data-driven decision that significantly improved a process or outcome. What was the problem, your approach, and the impact? How to answer: Use STAR. Focus on how you used data, your analysis, and the measurable results.
2) Describe a project where you applied statistical techniques to solve a business problem. What challenges did you face in data collection or interpretation, and how did you overcome them? How to answer: Detail the project, specific statistical methods used (e.g., hypothesis testing, regression), data quality issues, and how you ensured valid conclusions.
3) How do you approach forecasting for a new product or service where historical data is scarce? What data proxies or assumptions might you consider? How to answer: Discuss using analogous products, market research, pre-launch survey data, or qualitative expert opinion, and the caveats of each.
4) Amazon values “customer obsession.” Describe a time you used data to understand and improve a customer’s experience, even if it wasn’t explicitly requested. How to answer: Use STAR. Focus on your initiative to dive into data, identify a customer pain point, and propose/implement a data-backed solution.
5) Imagine you’ve built a predictive model, and the business team wants to understand its “black box” nature. How would you explain its key drivers and limitations to a non-technical audience? How to answer: Discuss interpretability techniques (e.g., feature importance, SHAP/LIME), simplifying complex terms, and focusing on actionable insights.
Interview Questions: Applied Scientist Intern
1) Describe a significant machine learning project you’ve worked on, from problem definition to model deployment. What was the most challenging technical hurdle, and how did you overcome it? How to answer: Use STAR. Detail the ML lifecycle, emphasizing your specific contributions and problem-solving skills for a technical challenge (e.g., data imbalance, model convergence, scalability).
2) Amazon encourages “invent and simplify.” Provide an example of a time you designed or significantly improved an algorithm or model, and how it simplified a complex system or process. How to answer: Focus on your innovative contribution to an algorithm, its technical novelty, and the practical simplification or efficiency gains it achieved.
3) If you were tasked with building a recommendation system for a new Amazon product category with very little user interaction data initially, what approach would you take to address the cold start problem? How to answer: Discuss strategies like content-based recommendations, hybrid models, leveraging user/item attributes, or using popularity metrics for initial recommendations.
4) Explain the architecture of a Deep Learning model you’re familiar with (e.g., CNN, RNN, Transformer). Why was this particular architecture suitable for the problem you were trying to solve? How to answer: Detail the components of the architecture and specifically link its design choices (e.g., convolutional layers for spatial patterns, attention mechanisms for long-range dependencies) to the characteristics of your problem.
5) Amazon operates at immense scale. How would you ensure the scalability and efficiency of an ML model or system you developed, particularly when dealing with high-throughput inference or large training datasets? How to answer: Discuss considerations like distributed training (e.g., Spark, Horovod), model quantization, efficient inference (e.g., ONNX, TensorRT), optimizing data pipelines, and cloud-native solutions (AWS).
About the Company | Amazon Internship Hiring 2025
Amazon is a global technology company known for its relentless customer obsession and pioneering spirit, striving to be Earth’s most customer-centric company. Its culture is built on a foundation of 16 Leadership Principles that guide daily work, from discussing new projects to making strategic decisions. Amazon fosters an environment where employees are encouraged to “Invent and Simplify,” “Think Big,” and show a “Bias for Action,” even embracing “failing fast” as a path to innovation.
The company is committed to building a diverse, equitable, and inclusive workplace, believing that varied perspectives drive the best solutions. Amazon invests heavily in its employees’ growth, offering resources for skill development, mentorship, and opportunities to work on projects that impact millions of customers globally. Interns at Amazon are treated as integral team members, gaining real-world experience by owning projects from start to finish within a fast-paced, agile development environment that deals with large-scale, multi-tiered, and distributed systems.
Conclusion | Amazon Internship Hiring 2025
These Data Scientist Intern and Applied Scientist Intern positions at Amazon in India offer incredible opportunities for students passionate about data, analytics, and artificial intelligence. If you possess a strong academic background, excellent problem-solving abilities, and a drive to innovate, these full-time internships are your gateway to making a significant impact.
You’ll gain invaluable hands-on experience, whether through deriving business insights from data or developing cutting-edge AI/ML algorithms for real-world applications. Don’t miss this chance to learn from a pioneer community and launch your career with a global technology leader committed to innovation and customer obsession.
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Frequently Asked Questions | Amazon Internship Hiring 2025
1) What educational backgrounds are preferred for these roles?
Ans: Computer Science, Engineering, Operations Research, Process Control, or related fields.
2) What are the key differences between the Data Scientist and Applied Scientist Intern roles?
Ans: Data Scientist focuses more on statistical analysis for business decisions and insights, while Applied Scientist focuses on developing and deploying advanced ML/DL/NLP/CV algorithms.
3) What programming languages are generally required?
Ans: Syntactical knowledge in C/C++, Python, Java, or Perl.
4) Are research publications beneficial for the Applied Scientist role?
Ans: Yes, published papers at top-tier conferences are preferred for the Applied Scientist Intern role.
Disclaimer | Amazon Internship Hiring 2025
The Recruitment Information Provided above is for Informational Purposes only. The above Recruitment Information has been taken from the official site of the Organization. We do not provide any Recruitment guarantee. Recruitment is to be done as per the official recruitment process of the company. We don’t charge any fee for providing this job Information.