Job Description
Company Description DataGOL is an AI-native data and agents platform that enables organizations to launch governed AI agents on enterprise data in days instead of months. The platform unifies data infrastructure, context management, and agentic capabilities, allowing teams to deploy AI internally and build AI-native products externally. DataGOL’s core components, DataOS and AgentOS, streamline semantic data modeling from structured and unstructured sources and support multi-agent orchestration that can be embedded into client products. Designed with enterprise-grade security and governance, DataGOL complies with SOC-2, HIPAA, and GDPR and supports deployments across private cloud, on-premise, and sovereign AI environments. The platform is built for regulated industries such as healthcare, event management and financial services etc., enabling firms to automate complex data workflows and achieve organization-wide intelligence.
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Role Description The Data Analyst Intern role at DataGOL is an on-site internship based in Princeton, NJ. The intern will support the data team by collecting, cleaning, and analyzing structured and unstructured data used across DataOS and AgentOS. Daily tasks include preparing datasets, building basic reports and dashboards, performing exploratory data analysis, and supporting the development of semantic data models. The intern will collaborate with engineers and product managers to translate business questions into analytical tasks, document findings, and communicate insights in a clear, concise manner. This role provides hands-on experience with AI-driven data workflows, exposure to enterprise data governance practices, and opportunities to contribute to internal and client-facing analytics initiatives.
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Qualifications
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- Strong analytical skills and foundational knowledge of data analytics methods.
- Understanding of statistics, including descriptive and inferential techniques.
- Experience or coursework in data modeling and working with structured datasets.
- Clear written and verbal communication skills for presenting insights and collaborating with cross-functional teams.
- Pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Familiarity with tools such as Excel, SQL, Python, or R for data analysis is beneficial.
- Interest in AI, data platforms, and enterprise data governance is a plus.
- Ability to learn quickly, work independently under guidance, and manage multiple tasks in a fast-paced environment.
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