Summer 2027 AI Data Science Consulting Internship

Location: Minneapolis, MN (Hybrid but based in MN for summer)

Dates: June 1 - August 20, 2027 (10–12 weeks)

Status: Internship | Full-Time | Paid

Eligibility: Undergraduate, Master’s, Graduate-Level or PhD Students

Extension: Potential extension; remote work may be considered

Role Overview

Elire is a trusted Oracle consulting partner with over 20 years of experience delivering ERP, EPM, HCM, and Treasury transformations. We invest in responsible, human-in-the-loop AI solutions that enhance our consultants and clients. This internship provides advanced students hands-on exposure to applied AI in a real consulting environment, with an emphasis on practical problem-solving and technical judgment.

The Opportunity

The AI Data Science Intern will focus on indexing, organizing, and structuring Elire documents and digital assets using graph-based concepts. This role is for a technically strong student who can help turn complex, distributed information into structured, connected knowledge to support AI-driven search, retrieval, reasoning, and consulting use cases.

Key Responsibilities

• Analyze Elire documents, assets, and information sources to identify entities, relationships, metadata, and structures.
• Support the design and development of graph-based approaches for indexing and connecting enterprise knowledge.
• Prepare, clean, normalize, and validate data used in AI, retrieval, and knowledge-graph workflows.
• Explore approaches involving embeddings, vectorization, semantic retrieval, property graphs, and related AI/data concepts.
• Build or support prototypes, scripts, data pipelines, or proof-of-value solutions using Python, SQL, and relevant data/AI tooling.
• Evaluate the quality, completeness, and usefulness of structured data and AI-generated outputs.
• Document data structures, assumptions, testing results, and technical findings.
• Collaborate with Elire AI, consulting, and technical leaders and present findings or a final project.

Requirements & Tech Stack

• Strong hands-on experience with Python and data manipulation, analysis, or modeling.
• Working knowledge of SQL and structured/unstructured data concepts.
• Understanding of graph concepts, knowledge graphs, property graphs, semantic relationships, or comparable data structures.
• Strong analytical ability and critical thinking.
• Ability to work through ambiguous technical problems with limited direction.
• Ability to evaluate results critically.
• Ability to communicate technical concepts clearly and professionally.

Qualifications

• Currently pursuing an Undergraduate, Master's or PhD in Data Science, Computer Science, Artificial Intelligence / Machine Learning, Analytics, Information Systems, Engineering, or a closely related technical field.

Preferred Qualifications

• Experience with graph databases or graph tooling (e.g., Neo4j).
• Exposure to LLM mechanics, embeddings/vectorization, RAG or semantic search, and generative AI APIs.
• Experience working with document corpora, metadata, enterprise search, or information retrieval.
• Exposure to cloud platforms such as Oracle Cloud, AWS, Azure, or GCP.
• Prior research, internship, or project experience involving applied AI, data science, or enterprise knowledge systems.

Who Will Be Successful

• Technically capable, curious, self-directed, and comfortable being challenged.
• Able to do the work, think critically, ask strong questions, and use AI as a tool without outsourcing technical judgment.