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APEX Analytix

SaaS-driven supplier risk management and audits

Data Science Intern

Applied Machine LearningUpdated on Nov 11
Internship · Summer 2027Greensboro, NC, USANo salary listedIn-person

About the Job

Requirements

  • Currently pursuing a bachelor's degree or higher in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field, or holding an associate degree with relevant skills and experience.
  • Have strong programming skills in Python and experience in data analysis, data science, or a related field.
  • Have experience with data analysis and machine-learning model development.
  • Have experience with SQL and database management systems.
  • Have knowledge of Large Language Models and their applications in AI product development.
  • Be familiar with containerization using Docker and Kubernetes.
  • Have problem-solving skills and the ability to work independently and collaboratively.
  • Have communication and documentation skills, including the ability to explain complex technical concepts to non-technical stakeholders.

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 the Kubernetes cluster.
  • Ensure the scalability, reliability, and performance of deployed applications.
  • Develop and integrate AI-powered product features using Large Language Models.
  • Troubleshoot and resolve issues related to AI applications, machine-learning models, and relevant tools and platforms.
  • Build user interface 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.

About the Company

APEX Analytix

SaaS-driven supplier risk management and audits

APEX Analytix provides supply chain risk management and recovery audit services for large enterprises, combining SaaS platforms with technology-enabled audits. Its tools, like smartvm for vendor data cleansing and apexarchimedes for data analytics, help automate supplier onboarding, risk assessment, and identify overpayments in the procure-to-pay cycle. Unlike firms that only advise, it offers end-to-end solutions that pair software with audits to reduce financial leakage and strengthen procurement controls. Its goal is to lower costs and improve financial performance by keeping a clean supplier database and tighter spend governance.

Company size
501-1,000
Company stage
Series A
Total funding
$7M
Headquarters
Greensboro, NC
Founded
1988

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