What are the responsibilities and job description for the Data Science Intern (Summer 2026) position at apexanalytix?
About Us
At apexanalytix, we’re lifelong innovators! Since the date of our founding nearly four decades ago we’ve been consistently growing, profitable, and delivering the best procure-to-pay solutions to the world. We’re the perfect balance of established company and start-up. You will find a unique home here.
And you’ll recognize the names of our clients. Most of them are on The Global 2000. They trust us to give them the latest in controls, audit and analytics software every day. Industry analysts consistently rank us as a top supplier management solution, and you’ll be helping build that reputation.
Read more about apexanalytix - https://www.apexanalytix.com/about/
Position Title: Internship – Data Science
Reports to: Manager- Data Science
Work Location: Greensboro, N.C.
Job Summary
The Data Science Intern is responsible for developing and deploying data analytics and AI applications, and developing machine learning models, deploying into Kubernetes clusters. This role involves working with large datasets, implementing monitoring systems, and post deployment analysis processes. The intern will be part of a dynamic team, driving our data-driven culture forward with innovative solutions.
Key Responsibilities
At apexanalytix, we’re lifelong innovators! Since the date of our founding nearly four decades ago we’ve been consistently growing, profitable, and delivering the best procure-to-pay solutions to the world. We’re the perfect balance of established company and start-up. You will find a unique home here.
And you’ll recognize the names of our clients. Most of them are on The Global 2000. They trust us to give them the latest in controls, audit and analytics software every day. Industry analysts consistently rank us as a top supplier management solution, and you’ll be helping build that reputation.
Read more about apexanalytix - https://www.apexanalytix.com/about/
Position Title: Internship – Data Science
Reports to: Manager- Data Science
Work Location: Greensboro, N.C.
Job Summary
The Data Science Intern is responsible for developing and deploying data analytics and AI applications, and developing machine learning models, deploying into Kubernetes clusters. This role involves working with large datasets, implementing monitoring systems, and post deployment analysis processes. The intern will be part of a dynamic team, driving our data-driven culture forward with innovative solutions.
Key Responsibilities
- Process and analyze complex data from diverse sources to extract business insights.
- Build and deploy machine learning models.
- Design, develop, and deploy containerized applications to our Kubernetes cluster.
- Ensure scalability, reliability, and performance of deployed applications.
- Work with Large Language Models (LLMs) to develop and integrate AI-powered features into our products.
- Troubleshoot and resolve issues related to AI applications and Machine Learning Models and the Relevant Tools/Platforms.
- Build UI applications using Streamlit or a similar framework to create product prototypes and gather user feedback.
- Stay up to date with industry trends, best practices, and emerging technologies in AI, data science, and cloud computing.
- Currently pursuing a bachelor's degree or higher in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field or Associate degree holders with relevant skills and experience.
- Strong programming skills in Python, with experience in data analysis, data science, or a related field.
- Experience with data analysis and machine learning model development.
- Experience with SQL and database management systems.
- Knowledge of Large Language Models (LLMs) and their applications in AI product development.
- Familiarity with containerization using Docker and Kubernetes.
- Excellent problem-solving skills, with the ability to work independently and collaboratively.
- Strong communication and documentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.