Data Science Internship

LexisNexis

. Analyze complex data sets and develop practical data mining and statistical analysis skills.

Posted 9/15/2026full-timeRaleigh • North Carolina • United StatesEntry Level💰 $22 - $34 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong analytical skills in data mining, statistical analysis, and machine learning, with a focus on model evaluation and AI output quality. Proficient in data visualization and effective communication of insights to support data-driven decision-making.

Highest-signal resume keywords

Python ProgrammingMachine LearningData VisualizationStatistical AnalysisAI Fluency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data MiningStatistical AnalysisExploratory Data AnalysisPredictive ModelingData CleaningModel EvaluationAnalytical Problem-SolvingData Quality AssessmentGenerative AILarge Language Models

Soft Skills

Effective CommunicationCritical ThinkingDetail-OrientedCollaborative WorkCuriosity

Tools & Technologies

RSQLData Science LibrariesNotebooksDashboards

Industry Keywords

Data ScienceAI-Enabled ProductsCustomer Impact MetricsResponsible AIData-Driven Decision-Making

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Analyze complex data sets and develop practical data mining and statistical analysis skills.
Contribute to machine learning and AI-enabled product solutions.
Explore model performance, data quality, retrieval quality, AI output quality, and customer-impact metrics.
Collect, clean, organize, and document 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 accuracy, grounding, relevance, reliability, bias, safety, and customer usefulness metrics.
Create visualizations, reports, dashboards, or notebooks communicating insights, experiment results, and model performance.
Document assumptions, limitations, evaluation methods, and responsible AI considerations for review, reproduction, and reuse by global teams.
Participate in weekly development sessions and gain exposure to data scientists, engineers, product managers, UX, and customer-focused teams.

Requirements

What you’ll need

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.
Applicants must have a graduation date AFTER June 2027 to be eligible for consideration.
Must work on-site in Raleigh, NC.
Relocation assistance is not provided.

Benefits

Comp & perks

This position is not eligible for benefits.