Job Summary

Amazon is seeking highly motivated, innovative, and detail-oriented interns to join our Big Data & AI teams. As an intern, you will work alongside experienced data scientists, machine learning engineers, and AI specialists to solve real-world challenges and help shape the future of our data-driven initiatives. This remote internship offers the opportunity to contribute to high-impact projects that touch millions of customers globally, while developing your skills in big data analytics, artificial intelligence, and cloud computing.

Key Responsibilities

• Collaborate with cross-functional teams to design, build, and optimize big data pipelines and AI models.
• Analyze large-scale datasets to extract meaningful insights and develop data-driven solutions.
• Assist in developing machine learning algorithms and deploying models into production environments.
• Support in data preprocessing, feature engineering, and exploratory data analysis.
• Conduct research on emerging AI technologies and present findings to technical stakeholders.
• Contribute to continuous improvement initiatives for data quality, scalability, and performance optimization.
• Document technical processes and provide recommendations based on your analyses and research.

Required Skills and Qualifications

• Currently enrolled in a Bachelors, Masters, or Ph.D. program in Computer Science, Data Science, Statistics, Artificial Intelligence, or related fields.
• Strong foundation in programming languages such as Python, Java, or Scala.
• Proficiency in SQL and experience working with large datasets.
• Solid understanding of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Excellent problem-solving skills and ability to work independently in a remote environment.
• Effective communication and presentation skills, both written and verbal.

Experience

• Previous internship or academic project experience in data science, machine learning, AI, or big data environments is preferred.
• Familiarity with cloud platforms (AWS preferred) and distributed computing (e.g., Spark, Hadoop) is a plus.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib is desirable.

Working Hours

• This is a full-time, remote internship opportunity.
• Flexible working hours, with the expectation of approximately 35-40 hours per week.
• The internship period is typically 10-12 weeks, with potential for extension based on project needs and performance.

Knowledge, Skills, and Abilities

• Strong analytical and critical thinking skills.
• High attention to detail and commitment to data integrity.
• Ability to manage multiple tasks and projects in a fast-paced environment.
• Passion for innovation and continuous learning in the fields of AI and big data.
• Team player with a collaborative mindset and a willingness to contribute to shared goals.

Benefits

• Competitive internship stipend.
• Mentorship from seasoned Amazon data scientists and AI professionals.
• Opportunity to work on impactful projects with cutting-edge technologies.
• Access to Amazons global learning and development resources.
• Networking opportunities with Amazon leadership and tech community.
• Flexible remote work environment with potential consideration for full-time roles post-internship.

Why Join

At Amazon, we are passionate about using technology to solve complex business challenges and improve customer experiences worldwide. As part of our Big Data & AI internship program, you will be empowered to innovate, experiment, and contribute to some of the most exciting projects in the industry. You will gain exposure to Amazons unique culture of ownership, customer obsession, and continuous learning. If you are ready to take your skills to the next level and make a tangible impact, we invite you to join our team.

How to Apply

Please submit your application via the Amazon Careers portal. Include your updated resume, a cover letter detailing your interest in the internship, and any relevant project or portfolio links. Shortlisted candidates will be contacted for an initial interview.