Data Scientist Intern

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.