Data Science Intern: Build Pipelines, Drive Insights

Q2 India; Austin (TX); On-site; USD 2,755,000 - 4,133,000; Part time

Job summary

Q2 invites driven students in Data Science, Statistics, or Computer Science to join as interns. You will work on end-to-end data science projects, from problem definition to prototyping and model support, while learning how data pipelines connect to user interfaces and systems.

Strong Python/SQL skills and ML coursework are expected, with Git familiarity encouraged. The role emphasizes curiosity, ownership, and collaboration in a fast-paced fintech context, with opportunities to engage in real

Qualifications

• Currently pursuing a degree in Data Science, Statistics, Computer Science, or a related field.
• Proficiency in Python and SQL.
• Coursework or project experience with machine learning algorithms and packages.
• Familiarity with Git or other version control tools.
• Curiosity, ownership, and a genuine interest in the field.
• Nice to have exposure to cloud-native or service-oriented architectures.
• Familiarity with the broader software development life cycle.

Responsibilities

• Help define problems and refine requirements alongside the team.
• Explore data, prototype solutions, and support model development.
• Learn how upstream data pipelines and downstream UIs connect to the systems you’re working on.
• Support testing, monitoring, and bug fixes, and help gather feedback to improve the product.

Skills

Python

SQL

Machine learning

Git

Curiosity

Cloud-native

SDLC

Education

Data Science / Statistics / CS degree student

Job description

Q2 invites driven students in Data Science, Statistics, or Computer Science to join as interns. You will work on end-to-end data science projects, from problem definition to prototyping and model support, while learning how data pipelines connect to user interfaces and systems.

Strong Python/SQL skills and ML coursework are expected, with Git familiarity encouraged. The role emphasizes curiosity, ownership, and collaboration in a fast-paced fintech context, with opportunities to engage in real