Intern Data Science

Company Description PPStack is a global EdTech organization focused on reimagining the future of education by equipping learners and professionals with skills needed for the digital era. The company blends artificial intelligence, modern technology, and innovative teaching methods to create smarter and more impactful learning experiences. PPStack bridges the gap between education and industry through future-ready skills, digital empowerment, and career transformation programs. Its ecosystem includes AI-powered learning platforms, crash courses, corporate training, career coaching, digital branding, technology consulting, and research in learning technologies, serving learners and organizations worldwide. PPStack is committed to driving transformation across education, careers, digital growth, and technology innovation.
Role Description As an Intern Data Science at PPStack, you will work full time in a remote capacity, supporting data-driven decision-making across educational and career solutions. On a day-to-day basis, you will collect, clean, and analyze structured and unstructured data from various platforms and programs. You will assist in building and evaluating statistical models, dashboards, and reports that provide insights into learner performance, engagement, and outcomes. The role includes collaborating with mentors and cross-functional teams to support data science projects, experiments, and pilots for AI-powered learning and career acceleration programs. You will document findings, prepare visualizations, and contribute to improving PPStack’s data pipelines and analytics processes.
Qualifications
Strong foundation in Data Science and Data Analytics, with the ability to apply concepts to real-world education and career-related problems.
Proficiency in Data Analysis and Analytical Skills, including interpreting results, identifying trends, and generating actionable insights.
Working knowledge of Statistics, including probability, hypothesis testing, regression, and basic experimental design.
Familiarity with programming languages commonly used in data science (such as Python or R) and data manipulation libraries (e.g., pandas, NumPy).
Experience or coursework in machine learning, data visualization tools (such as Tableau, Power BI, or matplotlib), and SQL is an advantage.
Currently pursuing or recently completed a degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related field.
Ability to work independently in a remote environment, manage time effectively, and collaborate with diverse, cross-functional teams.
Clear written and verbal communication skills, with an interest in EdTech, AI-driven learning, and career transformation initiatives.

Work arrangement
Yes