Excel Specialist

Engaging Excel Specialists to support a customer’s initiative focused on enhancing an LLM’s proficiency in creating, understanding, and modifying Office Open XML files - including complex .xlsx, .docx, and .pptx documents. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters.

- Minimum 3+ years of professional experience working in Fortune 500 environments using Excel, PowerPoint, and Word on high-impact business projects. - Demonstrated expertise in creating complex models, reports, analyses, and presentations across various industries such as finance, healthcare, tech, consulting, or retail. - Background in business roles such as private equity associate, investment banking analyst, junior consultant, FP&A analyst, HR, or marketing strategist, with hands-on involvement in deal or project work. - Proficiency in designing use cases reflecting functions like strategy, operations, sales, marketing, finance, or HR. - Exceptional written and verbal communication skills, with a keen eye for detail and clarity in articulating feedback. - Experience interacting with LLMs or writing long-form prompts for AI tools is a strong plus. - Strong analytical mindset and ability to evaluate nuanced differences in document quality and business applicability.

- Design and simulate challenging, realistic business scenarios that require expert-level use of Excel, PowerPoint, and Word, mirroring tasks from your professional experience. - Engage in structured, multi-turn conversations with an LLM, presenting complex document-related prompts and evaluating AI-generated deliverables. - Create and review Office documents (.xlsx, .docx, .pptx), assessing two AI-generated solutions against professional standards and selecting the preferred output. - Document feedback and provide detailed, side-by-side preference data to inform AI model improvements, focusing on quality, accuracy, and business relevance. - Contribute domain-specific insight across multiple industries and business functions, ensuring the data collected covers diverse, real-world use cases. - Communicate clearly and thoughtfully in both written and verbal formats to ensure precise understanding and actionable feedback for the AI training team.