actian - RevOps AI Analyst Intern
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Requirements
• We are looking for candidates who are passionate about the intersection of AI and business impact. • Educational Focus: Pursuing a degree (undergrad/masters) in Business Analytics, Data Science, Information Systems, or Business Administration. • AI & Knowledge Management: Experience using Generative AI (GenAI) tools and research assistants (e.g., NotebookLM, ChatGPT, or Claude) to synthesize complex documentation, extract insights from unstructured data, and build grounded knowledge bases. • SQL Fundamentals: Proficiency in writing queries to validate data and audit AI outputs. • Data Modeling: Understanding of relational databases, schema design, and Semantic Layer definitions. • BI & Analytics: Familiarity with Business Intelligence tools (e.g., Tableau, Power BI, or Looker) and data visualization principles. • Stakeholder Management: Ability to translate technical concepts for non-technical business users. • RevOps Familiarity: Experience with Salesforce (SFDC) architecture or revenue lifecycle concepts is preferred although not required • Problem-Solving: A product-owner mindset with the ability to synthesize user feedback into actionable technical insights. • Must be actively enrolled in a college degree program • Must be legally authorized to work in the United States
Responsibilities
• This is a unique opportunity to work at the intersection of Revenue Strategy and AI Implementation with high visibility across the organization. • Product Ownership & User Discovery • Stakeholder Engagement: Act as a junior Product Owner by conducting discovery interviews with cross-functional stakeholders (Sales, Marketing, and Product) to identify critical analytics "pain points" and high-value data gaps. • Requirements Synthesis: Translate qualitative user feedback into technical requirements for the AI Analyst, ensuring the conversational interface addresses real-world business logic. • Strategic Roadmap: Develop a forward-looking strategic roadmap for future AI iterations based on pilot insights, highlighting opportunities for scalability across the organization. • Data Architecture & Semantic Modeling • Semantic Layer Definition: Support the documentation of the Semantic Layer by building a standardized Metrics Definitions Glossary, ensuring the AI provides "one version of the truth." • Prompt Engineering: Design and curate a Prompt Library to optimize the AI’s Natural Language Processing (NLP) capabilities and improve the precision of generated insights. • Data Integrity & Validation: Utilize SQL and Salesforce (SFDC) reporting to audit AI-generated outputs, performing root-cause analysis on query failures to ensure data accuracy. • Pilot Management & Performance Analytics • Operational Execution: Manage the daily lifecycle of the Pilot program, serving as the primary lead for the "Steward Inbox" to monitor query failures and user friction points. • Success Benchmarking: Track and analyze Adoption Metrics—including Active Users, Question Success Rates, and Time-to-Insight—to quantify the pilot’s ROI and business impact. • Capstone Presentation: Synthesize complex data findings into a compelling narrative for the Internship Showcase, presenting your final recommendations to the Executive leadership team.
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