Applied Data Science Intern

Evolver•Palo Alto, CA

2d•Hybrid

About The Position

Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases. This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment. The internship is 10 weeks long (full-time), running from June through Early August. It offers competitive compensation tailored to experience and skill set. The format is hybrid (4+ days in person) and based in Palo Alto, CA. The cohort size is small and mentorship-focused. The learning goals are to develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Requirements

Graduate students with a record of excellence
Exceptional advanced undergraduates
Must be recommended by an accredited professor leading a relevant program at a top university (will be verified during application process).
Programming experience
Curiosity about AI systems and emerging technologies
Initiative, creativity, and strong problem-solving ability
Prior technical, research, or project experience
Intellectual curiosity, adaptability, and motivation to build

Responsibilities

Contribute to real data innovation projects involving data analysis and machine learning pipelines.
Work on AI agents, retrieval systems, and evaluation frameworks.
Engage with enterprise AI integration and deployment tooling.
Participate in product prototyping and applied research.
Develop automation systems for large-scale organizational use.
Explore real-world enterprise use cases of graph theory.
Gain direct exposure to Fortune 500 clients.
Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.
Work on projects oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.