Data Scientist Internship 2026

Introduction

In the IBM Chief Analytics Office, you will be part of a dynamic team driving the future of AI and data science in large-scale enterprise transformations. We offer a collaborative environment where your technical expertise will be valued and your professional development will be supported. Join us to work on challenging projects, leverage the latest technologies, and make a tangible impact on a leading organization.

Your role and responsibilities

Role Overview:
As a Data Scientist intern in IBM's Chief Analytics Office, you will be in a unique position to combine your strategic thinking with your technical skills in AI, machine learning, and data analytics. You will apply your skills to help implement data-driven solutions that align with business goals. You will steer enterprise projects that improve decision-making, solve complex problems, and drive business growth. This role involves working with team members and stakeholders to translate data insights into actionable recommendations that deliver meaningful business impact.

Key Responsibilities:

1. AI, Data Science, and Technical Execution:

• Support the design, implementation and optimization of AI-driven strategies per business stakeholder requirements.
• Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights.
• Apply GenAI, traditional AI, ML, NLP, computer vision, or predictive analytics where applicable.
• Collect, clean, and preprocess structured and unstructured datasets.
• Help refine data-driven methodologies for transformation projects.
• Learn and utilize cloud platforms to ensure the scalability of AI solutions.
• Leverage reusable assets and apply IBM standards for data science and development.
• Apply ML Ops and AI ethics.

• Translate business requirements into technical strategies.
• Ensure alignment to stakeholders' strategic direction and tactical needs.
• Apply business acumen to analyze business problems and develop solutions.
• Collaborate with stakeholders and team to prioritize work.

• Manage and contribute to various stages of AI and data science projects, from data exploration to model development to solution implementation and deployment.
• Use agile strategies to manage and execute work.
• Monitor project timelines and help resolve technical challenges.
• Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs.

• Communicate regularly and present findings to collaborators and stakeholders, including technical and non-technical audiences.
• Create compelling data visualizations and dashboards.
• Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems.

• Pursuing a Bachelor's degree in Computer Science, Data Science, Statistics, Economics, or a related field.
• Experience with AI/ML technologies and statistical modeling through coursework, projects, or past internships or full time positions.

• Proficiency in SQL and Python for performing data analysis and developing machine learning models.
• Experience and/or coursework in statistics, machine learning, generative and traditional AI.
• Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch.
• Familiarity with cloud-based platforms and data processing frameworks.
• Understanding of large language models (LLMs).
• Familiarity with object-oriented programming.
• Experience and/or coursework with common Python libraries used by data scientists (e.g., NumPy, Pandas, SciPy, scikit-learn, matplotlib, Seaborn, etc.)

• Strategic thinking and business acumen.
• Strong problem-solving abilities and eagerness to learn.
• Ability to work with datasets and derive insights.
• Attention to detail.

• Excellent communication skills, with the ability to explain technical concepts clearly.
• Independent and team-oriented.
• Understands AI Ethics principles.
• Works in an open and inclusive manner.
• Adaptable to fast-paced environments.
• Enthusiasm for learning and applying new technologies.
• Growth mindset.
• Ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment.