Data Scientist Intern: 2026

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Introduction

In IBM Business Platform Transformation, you will be part of a dynamic team shaping the future of AI and data science in large-scale enterprise environments. We offer a collaborative, learning-focused environment where your curiosity is encouraged, your growth is supported, and your contributions matter. This internship provides exposure to modern tools, real business challenges, and experienced mentors who will help you build a strong foundation for your career.

Role Overview

Your role and responsibilities

As a Data Scientist Intern in IBM Business Platform Transformation, you will be in a unique position to learn how strategic thinking and data-driven technology come together to solve real business problems. With guidance from experienced practitioners, you will apply foundational skills in AI, machine learning, and data analytics to support the development of solutions that align with business goals.

You will contribute to enterprise initiatives by helping analyze data, explore models, and translate insights into practical recommendations. This role is designed to accelerate your learning through hands-on experience, mentorship, and exposure to real-world AI-driven transformation projects.

Key Responsibilities

• AI, Data Science, and Technical Execution:
• Support the design and implementation of AI- and data-driven solutions based on clearly defined business requirements.
• Assist with developing and testing machine learning models or analytical approaches under guidance, from problem understanding through evaluation.
• Apply foundational techniques in GenAI, traditional ML, NLP, predictive analytics, or related areas where appropriate.
• Collect, clean, and preprocess structured and unstructured datasets using established tools and best practices.
• Learn and apply data science methodologies used in enterprise transformation projects.
• Gain exposure to cloud platforms and data tools, learning how scalability and deployment are supported.
• Leverage existing reusable assets and follow IBM standards for data science and development.
• Learn about ML Ops concepts and AI ethics principles and apply them under supervision.
• Strategic Planning
• Assist in translating business questions and requirements into technical tasks and analytical approaches.
• Learn how teams align technical work with stakeholder priorities and strategic goals.
• Apply developing business acumen to understand problems and contribute to solution ideas.
• Collaborate with team members to help prioritize and organize work.
• Project Management and Delivering Business Outcomes:
• Contribute to various stages of AI and data science projects, including data exploration, analysis, model development, and solution testing.
• Participate in agile ceremonies and learn how agile practices are used to plan and deliver work.
• Track assigned tasks and raise questions or risks early to mentors or teammates.
• Support measurement efforts by helping define or analyze basic metrics and KPIs used to evaluate solutions.
• Communication and Collaboration:
• Share progress, learnings, and results with teammates in a clear and professional manner.
• Assist in creating data visualizations, summaries, or dashboards to communicate insights.
• Work closely with data engineers, software developers, and other team members to understand how AI solutions fit into broader systems.
• Actively seek feedback and apply it to improve both technical and professional skills.
  
  

Required Technical And Professional Expertise

Required Education: Currently pursuing a Bachelor’s degree in Computer Science, Data Science, Statistics, Economics, Engineering, or a related field.

Experience

• No full-time experience required.
• Exposure to AI, ML, or data analytics through coursework, academic projects, personal projects, or prior internships is a plus.
  
  

Technical Skills

• Working knowledge of Python and SQL through coursework or projects.
• Introductory experience with statistics, machine learning, and AI concepts.
• Familiarity with common machine learning approaches (e.g., regression, decision trees, basic neural networks).
• Exposure to data science libraries such as NumPy, Pandas, scikit-learn, matplotlib, Seaborn, etc.Introductory awareness of large language models (LLMs) and generative AI.
  
  

Strategic And Analytical Skills

• Curiosity and interest in understanding business problems through data.
• Strong problem-solving mindset and eagerness to learn.
• Ability to work with datasets and identify basic patterns or insights.
• Attention to detail and willingness to iterate on work.
  
  

Communications And Soft Skills

• Ability to explain technical concepts clearly and simply.
• Comfortable working both independently and as part of a team.
• Awareness of AI Ethics principles and responsible technology use.
• Works in an open, inclusive, and collaborative manner.
• Adaptable and eager to learn in a fast-paced environment.
• Growth mindset with openness to feedback.
• Ability to manage time, prioritize tasks, and meet deadlines with support.
  
  

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

If you have questions about this posting, please contact [email protected]