Apply natural language processing (NLP) techniques to identify trends and patterns in unstructured text data such as surveys, support tickets, and call transcripts.
Develop and experiment with solutions using large language models (LLMs) to help automate and scale analytical processes.
Use machine learning and statistical methods to extract actionable insights from large, multi-dimensional customer behavior and usage datasets.
Communicate complex analytical concepts to non-technical audiences through clear written and verbal communication, supported by compelling data visualizations.
Document, gather, and share best practices and insights within the team to help promote a data-driven culture at Dropbox.
Collaborate proactively with stakeholders across Customer Experience and Success to understand business needs and support accurate and relevant analytical deliverables.

Requirements

Currently enrolled as an undergraduate (sophomore or above) or graduate student, majoring in Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or a related field.
Strong written and verbal communication skills, with the ability to explain technical concepts clearly.
Familiarity with data analysis workflows and foundational machine learning concepts.
Strong programming skills in Python, with experience using data science libraries such as pandas, NumPy, scikit-learn, or similar.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

natural language processinglarge language modelsmachine learningstatistical methodsdata analysisPythonpandasNumPyscikit-learn

written communicationverbal communicationcollaborationdata visualization