Data Scientist Intern 2027

We are seeking enthusiastic and driven interns to join the AI, Automation, and Data Platforms (AADP) team at IBM CIO. As an intern, you will play a critical role in developing cutting-edge solutions using Watsonx LLMs (Large Language Models), Watsonx Orchestrate, Milvus, and other state-of-the-art technologies. You will work closely with cross-functional teams to integrate these solutions into business processes, orchestrate various components, and build scalable solutions leveraging automation, AI, and data technologies.

This role requires a strong understanding of business needs and the ability to translate them into technical stories to guide development: Hands-on experience working with IBM's cutting-edge technologies, including GenAI (Watsonx.ai platform), LLM technologies, vector databases (Watsonx.data), and automation tools (Watson Orchestrate). Opportunities to enhance your programming skills, critical thinking, and problem-solving abilities. Exposure to real-world challenges in AI orchestration, automation, and business-driven development.

Experience working in a dynamic, innovation-focused environment alongside leading experts in AI, automation, and data platforms. Networking opportunities within IBM's global business and technology ecosystem.

Role Overview

As a Data Scientist intern in the AI, Automation and Data Platform organization, 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

• 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.
• Strategic Planning 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.
• Project Management and Delivering Business Outcomes: 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.
• Communication and Collaboration: 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.

Technical Skills

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