Data Scientist Intern

Job Description

We are looking for enthusiastic and driven interns to join the AI, Automation, and Data Platforms (AADP) team at IBM CIO. As an intern, you will help develop cutting-edge solutions using Watsonx LLMs, Watsonx Orchestrate, Milvus, and other advanced technologies. You will collaborate with cross-functional teams to integrate these solutions into business processes, orchestrate components, and build scalable solutions using 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.

What You'll Gain

• Hands-on experience 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 programming skills, critical thinking, and problem-solving abilities.
• Exposure to real-world challenges in AI orchestration, automation, and business-driven development.
• Experience 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 combine strategic thinking with technical skills in AI, machine learning, and data analytics. You will help implement data-driven solutions aligned with business goals, steer enterprise projects that improve decision-making, solve complex problems, and drive business growth. You will work 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. 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 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 with 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 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.

Qualifications

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 data analysis and machine learning model development.
• 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.