Data Science Internship

About the role

As a Data Science Intern, you will analyze complex data sets, develop practical data mining and statistical analysis skills, and contribute to machine learning and AI-enabled product solutions. You will work closely with data scientists and engineers to explore model performance, data quality, retrieval quality, AI output quality, and customer-impact metrics for products that use trusted legal and professional content. You will help evaluate and improve AI-powered experiences while building valuable hands-on skills in data science, machine learning, and responsible AI practices. The internship starts June 7, 2027, lasts 11-12 weeks, is on-site in Raleigh, NC. Relocation assistance is not provided. Applicants must have a graduation date after June 2027 to be eligible.

Responsibilities

• Contribute to collecting, cleaning, organizing, and documenting datasets for analysis, model development, and evaluation.
• Collaborate with data science, engineering, product, and UX team members to develop, test, and improve predictive models, machine learning workflows, and AI-enabled product capabilities.
• Conduct exploratory data analysis to identify trends, patterns, data-quality issues, and opportunities to improve customer outcomes.
• Support experiments involving generative AI, large language models, embeddings, retrieval-augmented generation, prompt patterns, and agentic workflows.
• Contribute to model and AI-output evaluation, including metrics for accuracy, grounding, relevance, reliability, bias, safety, and customer usefulness.
• Create visualizations, reports, dashboards, or notebooks that communicate insights, experiment results, and model performance clearly.
• Document assumptions, limitations, evaluation methods, and responsible AI considerations so work can be reviewed, reproduced, and reused by global teams.

Requirements

• Be a currently enrolled student pursuing a degree in data science, computer science, statistics, mathematics, engineering, or a related field of study.
• Have experience using programming languages and tools such as Python, R, SQL, notebooks, and common data science libraries.
• Demonstrate a foundation in statistics, machine learning, data visualization, and analytical problem-solving.
• Demonstrate AI fluency or curiosity, including awareness of generative AI, large language models, embeddings, RAG, model evaluation, model limitations, and responsible AI practices.
• Demonstrate effective problem-solving, critical-thinking, verbal, and written communication skills.
• Be detail-oriented and able to work both independently and collaboratively with others.
• Demonstrate an interest in learning, experimentation, data-driven decision-making, and staying current with AI and data science trends.

Pay

$22-$34 per hour, depending on the level of the degree.