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New York, United States

Internship

Hybrid

Intern

IBM is a leader in business platform transformation, focusing on AI and data science in enterprise environments. As a Data Scientist Intern, you will learn to apply foundational skills in AI, machine learning, and data analytics to solve real business problems under the guidance of experienced practitioners.

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Responsibilities

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
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
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
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

Qualification

Required

Currently pursuing a Bachelor's degree in Computer Science, Data Science, Statistics, Economics, Engineering, or a related field
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
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
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

Preferred

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