AI Intern - QuantumBlack, AI by McKinsey

Descripción del puesto:

As an AI Intern at QuantumBlack, you'll join a multi-disciplinary team that uses data and artificial intelligence to create real-world impact for leading organizations around the world.

In this role, you will support both data science and data engineering activities, gaining hands-on experience across the full data and AI workflow. You'll help explore and prepare datasets, support the development of scalable ML and GenAI models, and contribute to building data pipelines that enable advanced analytics. You will also gain visibility into the full lifecycle of AI and GenAI projects, from understanding the business problem to developing, validating, and deploying solutions.

Working closely with data scientists, data engineers, ML engineers, software engineers, and project managers, you will learn how to translate complex questions into analytical approaches, interpret results in a business context, and help teams drive meaningful impact across different industries.

Throughout your internship, you will:

* Assist in data exploration, preparation, modeling, and experimentation with GenAI techniques
* Contribute to building and maintaining data pipelines and cloud-based environments
* Apply Python, SQL, and modern data/ML tools such as PySpark, Databricks, Airflow, and Kedro
* Present your work, receive continuous feedback, and grow your technical, analytical, and problem-solving skills

You will be part of our São Paulo office and collaborate with colleagues across QuantumBlack's global network. From day one, you'll be supported by mentors and a community that values curiosity, learning, and experimentation, giving you the space to ask questions, try new approaches, and develop both technically and professionally.

Please submit your CV in English

Requerimientos del candidato/a:

* Currently pursuing a bachelor's degree in computer science, Engineering, Statistics, Mathematics, Physics, or a related field (expected graduation between December 2026 and July 2027)
* Foundational knowledge in programming and data manipulation (e.g., Python and SQL)
* Interest in both data science and data engineering, with basic exposure to topics such as statistics, machine learning, data modeling and data pipelines
* Strong analytical thinking and problem-solving skills, with the ability to break down complex problems into structured steps
* Curiosity to learn new tools and technologies in areas such as cloud computing, data processing frameworks (e.g., Spark), and modern ML techniques
* Ability to work collaboratively in multi-disciplinary teams and communicate clearly with colleagues from technical and non-technical backgrounds
* Ability to communicate ideas effectively, both verbally and in writing, in English and Portuguese