Agrocorp International is exploring the use of AI-assisted tools to support internal research and analysis workflows across commodity markets. As part of this initiative, we are looking for a detail-oriented Research Integrity intern to assist in evaluating the quality and accuracy of AI-generated research outputs.
This is a quality assurance and fact-checking role. You will not be building AI systems — you will be stress-testing their outputs against real-world data, with the goal of identifying where and why they fail.
WHAT YOU WILL DO
Primary Responsibility
Source-verify every factual claim against primary sources — exchange data, central bank publications, macro data releases, and price feeds.
Classify discrepancies by type: incorrect data, outdated information, calculation errors, or misleading framing.
Maintain a structured audit log documenting each finding, its source, and its potential impact on downstream decisions.
Escalate material errors promptly, as outputs may inform time-sensitive business decisions.
Secondary Responsibility
After an initial audit period, you will contribute to a summary findings report identifying recurring error patterns, high-risk output categories, and recommendations for improving output reliability.
WHAT WE ARE LOOKING FOR
Required
Foundational understanding of financial or commodity markets — enough to assess whether a data point is plausible.
Comfort with basic financial arithmetic: percentage changes, spreads, and unit conversions.
Methodical research habits — ability to locate and cite primary sources rather than rely on secondary summaries.
Preferred
Exposure to commodity or FX markets (agricultural products, energy, or major currency pairs).
Basic Python proficiency — sufficient to run scripts and record outputs in structured formats.
Familiarity with macro data calendars (central bank meetings, economic data releases).
Not Required
Prior experience with AI or machine learning.
Derivatives or options knowledge.
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