Data Science Intern (Morrisville, NC, US)

Job Summary

NetApp’s Active IQ Artificial Intelligence and Machine Learning power of predictive and prescriptive analytics enables customers and partners to automate data center operations and achieve extremely low total cost of ownership and avoid issues before they become a reality. Today, 98% of technical issues with NetApp products are automatically identified by Active IQ with prescriptive steps to avoid the issue – and we simply want to do better and more. Every day, one-half million active IOT end points feed the Active IQ multi-petabyte data lake with structured and unstructured data. That’s the pool you will have at your fingertips to continue to enhance NetApp’s world class data visionary analytic capabilities. 

 
As an intern on the Active IQ Data Science team, you will analyze customer meta-data and build high-end analytical models for solving high-value business problems, such as storage and IT ecosystem durability and health, network robustness, and enabling always on always available storage ecosystems. 

 
At NetApp, our products and solutions enable customers to unleash the power of their data. In the Active IQ team, we unleash the power of our own data at NetApp. 

Responsibilities:     

• Processing and analyzing large volumes of data. 
• Building predictive models with advanced machine learning algorithms such as Neural Networks, Decision Trees, Boosting/Ensemble methods, Clustering, etc. 
• Implementing data quality checks to ensure that all reporting and modeling is using correctly sourced data. 
• Interacting with business teams from the data analysis stage to the final report presentation. 
• Assisting Product Managers as needed to define and refine business use cases. 
• Writing coherent reports and making presentations on high-end analytical projects. 
• Communicating verbally and in writing with peer technical team members as well as business leaders. 
• Assist in building or integrating Generative AI–powered features, such as intelligent assistants, automation workflows, or recommendation systems. 
• Gain exposure to agentic frameworks and patterns (e.g., tool-using agents, multi-step reasoning, orchestration of AI agents). 

Job Requirements

• Experience in Machine Learning, Scripting, and Statistical & Reporting tools (Python, R, SQL, etc.). 
• Knowledge of at least some supervised and unsupervised modeling techniques such as Logistic/Linear Regression, SVMs, Neural Networks / Deep Networks, Boosting/Ensemble methods, Decision Trees, Clustering, etc. 
• Awareness of Generative AI concepts, including large language models (LLMs), prompt engineering, or AI-assisted development tools. 
• Willingness to extend beyond core data science work to perform -data wrangling, data prep and data transfers, data quality checks, deployment, monitoring 
• Ability to communicate clearly across data science team members 
• Experience with SQL and relational databases 
• Experience with unstructured and semi-structured data sources and requisite processing tools. 

Additional Skills and Abilities: 

• Excellent written and verbal communication skills. 
• Ability to think analytically, write and edit technical material, and relate statistical concepts and applications to technical and business users. 
• Ability to work both independently and in a team environment. 
• Exposure to Generative AI frameworks or libraries (e.g., LangChain, Semantic Kernel, OpenAI/LLM SDKs, vector databases). 
• Understanding of agentic design patterns, such as chaining, tool calling, memory, or task orchestration. 

Preferences: 

• Experience in mathematical/statistical modeling, pattern recognition, or data mining/data analysis. 
• Experience specifying, building, and maintaining advanced analytic solutions with large-scale transaction data. 
• Experience working in a team to perform data management, deployment and product support for advanced analytic solutions. 
• Experience building solutions that leverage Large Language Models. 
• Interest in building software that leverages Generative AI, intelligent agents, and automation to improve developer and customer experiences. 
• Ability to translate model performance to benefit for the business by incorporating knowledge of business owner practices and needs. 

Education

Must be enrolled in an educational or professional program through summer 2026 or later, preferably working towards a bachelor’s or master’s degree in data science & Statistics / Mathematics or related field.