Heading

Research Park, CA

Internship

Hybrid

Intern

IBM is a leading organization in AI and data science, offering a collaborative environment for its employees. As a Data Scientist intern in the Chief Analytics Office, you will apply your strategic thinking and technical skills to implement data-driven solutions that align with business goals, improving decision-making and driving business growth.

Apply Now

Responsibilities

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.

Qualification

Required

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.