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.