Intern Data Scientist 2027 – AI & Data Analytics

About the role

Launch your career like an IBMer. As an IBM intern, you'll contribute to real client projects across diverse industries, including analytics, AI adoption, generative AI, and agentic AI-enabled transformation. You'll develop technical expertise and consulting skills in a culture built on continuous learning, mentorship, and coaching. High-performing interns have a clear pathway into IBM's Associate Program.

Responsibilities

• Build data science and AI skills by contributing to client projects using statistics, machine learning, data science, GenAI, and agentic AI solution patterns.
• Develop a compelling portfolio, acquire new skills, and gain insight into diverse industries while contributing to client-ready analytical and AI solution components.
• Strengthen technical, analytical, and consulting skills while learning responsible AI practices.

Work Experiences You Could Be Exposed To

• Mentored Analytical Support: Receive mentorship from data scientists, AI engineers, consultants, and technical mentors while applying analytical rigor, statistical methods, and responsible AI practices to client challenges.
• Data Science and AI Development: Develop skills in writing efficient, reusable code to prepare data, build features, test models, and contribute to GenAI, RAG, or agentic AI solution components.
• Effective Communication: Assist in explaining analytical results, model behavior, assumptions, limitations, and recommendations to both technical and non-technical audiences.
• Tech-Driven Problem Solver: Use tools such as Python, SQL, notebooks, cloud platforms, APIs, data platforms, and AI-assisted coding tools to analyze data and help turn ideas into working analytical or AI assets.

Requirements

• Currently pursuing a quantitative degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, AI/ML, Cognitive Science, or a related field.
• Strong interpersonal skills that enhance collaboration and relationship building, while managing dynamic workloads in an agile environment.
• Initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset.
• Demonstrated leadership experience and ability to communicate effectively through active listening.
• Familiarity with programming and analysis tools such as Python, SQL, R, or similar.
• Willingness to travel as needed.

Preferred Qualifications

• Familiarity or interest in statistical analysis, machine learning, data mining, GenAI, RAG, or agent-based applications through internships, coursework, personal or academic projects, hackathons, and/or publications.
• Experience using machine learning, data science, or AI frameworks such as pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, LangChain, LangGraph, LlamaIndex, MCP-based tooling, or similar tools.
• Familiarity with AI-assisted coding and developer tools such as GitHub Copilot, Codex, Claude Code, Cursor, or similar tools for coding, testing, debugging, documentation, and code review.