Data Science Intern

Bertelsmann-Jobs•New York, NY

About The Position

Bertelsmann Education Group is seeking a curious and driven Data Science Intern to join its New York-based Data Lab. The intern will support digital transformation initiatives across education data and the development of data-driven solutions for portfolio companies, including Relias, Alliant University, and Afya. The role provides hands-on experience developing and experimenting with data science and machine learning prototypes, predictive modeling, advanced analytics, and modern AI techniques. Projects may explore user outcomes, engagement, and personalization, with the goal of turning data into actionable insights and improving user success. The intern reports to the Bertelsmann Education Group’s Data Strategy and Growth Manager and collaborates with data scientists, analysts, and business stakeholders. This is a part-time internship. The hourly rate is $19.00 USD.

Requirements

  • Currently pursuing or recently completed an M.Sc. or Ph.D. in Data Science, Computer Science, AI, Statistics, Engineering, Applied Mathematics, or a related field.
  • Proficiency in Python, including pandas, numpy, and scikit-learn, and SQL.
  • Familiarity with data pipelines, APIs, or integrating data from multiple sources.
  • Hands-on data science and machine learning experience through internships, coursework, or research projects.
  • Experience using GitHub for version control.
  • Strong problem-solving, collaboration, and communication skills.
  • Authorization to work in the United States.

Nice To Haves

  • Interest in experimenting with LLMs, simple agent workflows, or AI prototypes (POCs).
  • Experience with a BI tool such as Microsoft Power BI or Tableau.
  • Experience in education.
  • Familiarity with R.

Responsibilities

  • Support development of data science and machine learning prototypes (POCs) using education data.
  • Work with structured and unstructured datasets to generate insights and support decision-making, including marketing and academic data.
  • Develop and apply predictive and segmentation models to improve user engagement and outcomes.
  • Contribute to experimentation efforts, such as A/B testing, and translate results into actionable recommendations.
  • Build and iterate on data-driven solutions, including models and basic agent-based workflows.
  • Communicate findings and present insights to technical and non-technical stakeholders.
  • Collaborate with cross-functional teams and participate in knowledge-sharing and training sessions.
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