IT Commercial Systems, Data & AI Intern-Summer 2027

What you'd do

• Partner with business stakeholders to understand business problems and help document business requirements, current-state workflows, use cases, success criteria, and evaluation criteria for critical business technology initiatives.
• Support technology and platform evaluations by researching potential solutions, comparing capabilities against defined business requirements, and helping develop structured evaluation materials and recommendations.
• Help identify, document, and evaluate high-value AI and automation use cases based on business value, feasibility, data readiness, risk, adoption considerations, and implementation complexity.
• Support the definition and development of data products by identifying users, required data sources, business rules, metrics, data quality expectations, and desired business outcomes.
• Research and evaluate AI platforms, models, agents, applications, and emerging technologies for potential applicability to Xeris business needs.
• Support rapid prototypes, pilots, and proofs of concept using approved AI, analytics, automation, and data tools.
• Perform exploratory analysis of business data to identify trends, data quality issues, opportunities, and insights that support business decisions.
• Assist with data governance activities, including documenting data definitions, metadata, business rules, data lineage, ownership, and data quality requirements.
• Map current-state business processes and identify opportunities to simplify, automate, or redesign workflows using data, AI, and technology.
• Help define key performance indicators and measurement approaches for pilots, data products, and technology investments to determine whether solutions are delivering expected value.

What they want

• Undergraduate or graduate candidate pursuing a degree in Data Science, Computer Science, Information Systems, Analytics, Artificial Intelligence, Engineering, Business Analytics, or a related field.
• Minimum GPA 3.0.
• Returning to an academic program at a credentialed institution for at least one semester post-internship.
• Strong analytical and problem-solving skills with an interest in the intersection of business, data, AI, and technology.
• Ability to break down ambiguous business problems and organize information into clear requirements, analyses, or recommendations.
• Basic familiarity with data concepts such as relational data, analytics, visualization, APIs, data pipelines, or data quality.
• Familiarity with artificial intelligence, generative AI, large language models, machine learning, or automation concepts is preferred but not required.
• Exposure to SQL, Python, Power BI, Snowflake, or similar data and analytics technologies is a plus.
• Basic understanding of Agile methodologies and product development lifecycles
• Strong written, verbal, and presentation skills.