Quantum Data Scientist Intern - 2027

IBM Quantum is building the world’s leading quantum computing systems, software, and cloud services. The Data Analytics & Engineering Team plays a critical role in enabling data-driven decision making across the IBM Quantum organization by developing scalable data platforms, trusted analytics solutions, and actionable insights. As a Data Scientist Intern, you will work at the intersection of data science, analytics engineering, and data platform development.

You will partner with stakeholders across Product, Engineering, Client and Community, and Business Operation Teams to help transform data into meaningful insights that drive strategic and operational decisions. This role offers a unique opportunity to contribute to both the technical foundation of IBM Quantum's analytics ecosystem and the analytical products that support a rapidly growing business. As a Data Scientist Intern, you will:

• Support the design, development, and enhancement of IBM Quantum's scalable data and analytics platform.
• Develop data models, dashboards, reports, and self-service analytics solutions that enable informed decision making.
• Apply analytics engineering best practices to improve data reliability, consistency, governance, and accessibility. Perform advanced data analyses to identify trends, opportunities, and actionable business insights.
• Collaborate with internal teams such as Product, Engineering, Client Success, Community, Marketing teams to understand business requirements and translate them into analytical solutions.
• Assist in designing and implementing data pipelines and transformations to support reporting and analytical use cases. Communicate findings and recommendations through clear visualizations, presentations, and written analyses tailored to both technical and non-technical audiences.
• Contribute to documentation, knowledge sharing, and continuous improvement of the team's analytics and data engineering practice Experience working with Python (and common data science libraries such as Pandas, NumPy, scikit-learn) and SQL for data analysis, transformation, and querying large datasets. Experience with statistical modeling, forecasting, experimentation, or machine learning techniques. Strong analytical and problem-solving skills with the ability to navigate ambiguous business questions and deliver insights with limited guidance. Ability to work collaboratively in a cross-functional environment with both technical and business stakeholders. Excellent written and verbal communication skills. Experience with analytics engineering practices and tools such as dbt or similar transformation frameworks. Exposure to Airflow, Apache Spark, Presto/Trino, or similar data ecosystem technologies. Experience working with large-scale event, product, customer, or operational datasets. Knowledge of Git, software development best practices, and CI/CD workflows. Prior internship, research, open-source, or project experience involving data science, analytics engineering, or data platform development. Interest in quantum computing, emerging technologies, and data-driven product development.