Data Analytics Computer Science Internship Quality Intelligence Dashboard Jobs

In this Data Analytics | Computer Science internship: quality intelligence dashboard, you will help transform inspection and quality data into actionable business

Validate dashboard calculations, metrics, and data quality with stakeholders.

In Computer Science | Information Technology internship: automation and dashboard development, you will help transform these activities into efficient, standardized

Science, Data Science, Statistics, Mathematics, Engineering, Business Analytics, or a related field Cumulative GPA of 3.0 or higher Coursework or

degree in Data Analytics, Data Science, Computer Science, Engineering, or a related field Comfortable writing SQL queries to calculate metrics and pull

…To be suitable for the internship, you: Are pursuing a bachelor's or master's degree in Computer Science, Software

engineering, data science, applied mathematics, operations management, business analytics, computer science, or a related engineering discipline.

About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together.

About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together.

degree in Data Analytics, Data Science, Computer Science, Engineering, or a related field Comfortable writing SQL queries to calculate metrics and pull

Engineering, Computer Science, Data Science, Business Information Technology, or a related field; Have programming experience with Python, Django, or similar

Implement data validation processes and quality checks to ensure accuracy and reliability.

…To be suitable for the internship, you: Are pursuing a master’s degree in Computer Science, Data Science, Artificial

Example projects include building data quality checks for payment flows, creating dashboards to surface aging balance trends, automating compliance reporting, or

Work with Data Engineering to improve the quality and usability of underlying data, and develop reusable analytical models and workflows that reduce