Quest Analytics Internship Program Summer 2027 in Kansas City

Were looking for talented and curious students to join our Summer 2027 Technology Internship Program across three areas:

Software Engineering Contribute to the full software development lifecycle by helping plan design develop test and deploy features and applications that support our healthcare technology solutions. Work alongside experienced engineers to write quality code troubleshoot issues and improve existing products and functionality. Gain hands-on experience using modern AI-assisted development tools including Claude Code to support coding debugging testing documentation and development workflows.

Data Engineering Help build maintain and improve the data infrastructure that powers our products and analytics solutions. Work with large complex datasets to support daily data operations develop and optimize data ingestion pipelines automate data processes and monitor and troubleshoot data workflows to ensure reliable high-quality data. Explore opportunities to use AI-assisted tools including Claude Code to accelerate development automate workflows and improve engineering efficiency.

Data Science Apply statistics machine learning and AI to explore complex healthcare data and solve real-world business problems. Support data exploration model development and evaluation experimentation and the communication of analytical findings. Work with emerging technologies including generative AI Large Language Models (LLMs) and AI-assisted development tools such as Claude Code to explore new approaches to analytics and problem solving.

Interns will be aligned to a team and project based on their skills interests academic background and business needs.

Were looking for students who are already experimenting with AI not just learning about it in the classroom. Strong candidates will have hands-on experience usinggenerative AI and AI-assisted development tools through coursework personal projects research internships hackathons or other practical applications.

Experience may include tools and technologies such as Claude Claude Code LLMs prompt engineering AI-assisted coding RAG embeddings vector search AI agents or other applied AI/ML technologies.

Were especially interested in students who can demonstrate how theyve used AI to build something solve a problem automate a process analyze data or improve the way they workand who are curious about continuing to experiment with emerging technology.

• Must live in the Kansas City metro area
• Able to work without visa sponsorship now and in the future

• Pursuing a Bachelors or Masters degree in Computer Science Software Engineering Data Science Data Analytics Data Engineering or related field
• Juniors and above preferred (2 years of degree experience)
• Prior internship experience in data engineering analytics or data science is a plus

• Programming: Python and SQL
• Additional languages: C#/.NET preferred; Java or C also relevant
• Databases: SQL Server and relational databases; exposure to NoSQL or MongoDB is a plus
• Data & Development Tools: Databricks Spark Git
• Analytics & Visualization: Excel Power BI PowerPoint
• Frontend Development: HTML CSS/Sass React and TypeScript are a plus for Software Engineering candidates

• Understanding of object-oriented programming concepts; C#/.NET experience is preferred
• Ability to troubleshoot and debug applications
• Ability to write performant SQL queries against complex data models
• Understanding of relational databases data structures and software development fundamentals
• Exposure to data pipelines ETL/ELT processes distributed data processing APIs or cloud-based technologies is a plus
• Familiarity with source control and collaborative development using Git

For candidates interested in the Data Science track were also looking for exposure to or interest in:

• Statistics probability and exploratory data analysis
• Machine learning fundamentals including supervised and unsupervised learning
• Classification and regression techniques
• Model development validation and evaluation
• Feature engineering and data preprocessing
• Natural language processing (NLP)
• Python data science libraries such as pandas NumPy scikit-learn or similar tools
• Data visualization and communicating analytical findings
• Experimentation hypothesis testing and quantitative problem solving
• Generative AI and Large Language Models (LLMs) are a plus
• Exposure to prompt engineering embeddings vector search retrieval-augmented generation (RAG) or other applied AI techniques is a plus

• Strong communication and collaboration skills
• Ability to communicate data topics and results clearly
• Self-motivated proactive and effective in a remote environment
• Strong problem-solving mindset and team player attitude