AI Execution & Prototyping Analyst

📍 Job Overview

Job Title: AI Execution & Prototyping Analyst

Company: ASM Global (Legends Global)

Location: Frisco, TX, United States (Remote considered)

Job Type: Full-time

Category: Data & Analytics / Technology

Date Posted: 2026-09-15

Experience Level: Mid-Level (2-5 years)

Remote Status: Remote OK

🚀 Role Summary

• This role focuses on the rapid development and prototyping of interactive data visualizations and internal web applications using AI-assisted coding tools, specifically Anthropic's Claude ecosystem.

• It's a hands-on, builder-oriented position that bridges raw data and decision-makers through custom-built, AI-powered software solutions, moving beyond traditional BI dashboards.

• The analyst will translate ambiguous business questions into functional, interactive tools and potentially production-grade applications within tight feedback loops.

• Key activities include connecting directly to live data sources via integrations like MCP and owning the full lifecycle of visualization products from concept to deployment.

📝 Enhancement Note: The job title "AI Execution & Prototyping Analyst" and the description emphasize a shift from traditional Business Intelligence (BI) roles. The core function involves using AI coding agents (Claude Code) as a primary development environment, requiring a blend of coding proficiency, data understanding, and product thinking. This is not a standard data analyst role; it's more akin to a full-stack developer focused on data-driven applications, leveraging AI for speed and efficiency. The "Legends Global" branding suggests a focus on live events, venues, and sports, implying that data analysis will likely support these domains.

📈 Primary Responsibilities

• Rapidly prototype interactive data visualizations and internal web applications using Claude Code, focusing on tight feedback loops with stakeholders to iterate quickly.

• Translate stakeholder inquiries and ambiguous business questions into functional visual tools, such as dashboards, calculators, exploratory data apps, and simulations, bypassing traditional BI development cycles.

• Develop validated prototypes into production-quality web applications, ensuring proper data pipelines, authentication, hosting, and performance optimization.

• Connect visualizations directly to live data sources (databases, APIs, internal tools) leveraging Model Context Protocol (MCP) integrations, moving away from static data exports.

• Manage the entire lifecycle of a visualization product, from initial scoping and building to deployment, user feedback collection, and subsequent iterations.

• Write and maintain clean, efficient front-end code (JavaScript/TypeScript, React), often generated and refined in collaboration with Claude Code, rather than solely relying on drag-and-drop BI platforms.

• Establish and maintain reusable patterns, components, and internal libraries to accelerate the development of future prototypes and applications.

• Collaborate closely with data engineering teams to ensure the accuracy, governance, and reliability of the underlying data feeding into the applications.

• Act as an evangelist and trainer for other analysts, promoting AI-assisted, code-first visualization workflows as a modern alternative to legacy BI tools.

📝 Enhancement Note: The responsibilities clearly outline a product-centric approach to data visualization. The emphasis on "rapidly prototype," "hours or days, not weeks," and "shipping a rough version fast" points to an agile, iterative development methodology. The direct involvement with stakeholders and ownership of the "full lifecycle" indicate a high degree of autonomy and responsibility for the analyst. The mention of "production-quality" implies that these are not just throwaway prototypes but can become integral internal tools.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a Bachelor's degree in Computer Science, Data Science, Information Technology, or a related quantitative field is typically expected for roles involving significant coding and data analysis. Equivalent practical experience will also be considered.

Experience: Minimum of 2-5 years of experience in building data visualizations or internal tools, with a strong preference for candidates who have a significant track record of writing actual code rather than relying exclusively on point-and-click Business Intelligence (BI) platforms.

Required Skills:

• Agentic Coding Expertise: Regular and proficient use of Claude Code for prototyping, building, and deploying interactive web applications and visualizations.

• Front-End Development: Solid understanding of JavaScript/TypeScript and core front-end development principles, with experience in React or similar frameworks.

• Data Manipulation & Querying: Working SQL skills for data extraction and shaping from databases and APIs.

• Version Control: Familiarity with version control systems, particularly Git, for collaborative development and code management.

• Integration Awareness: Understanding of Model Context Protocol (MCP) or similar mechanisms for connecting AI tools to external systems and APIs.

• Data Visualization Libraries: Experience with charting and visualization libraries such as D3, Recharts, Plotly, or Chart.js.

• UX/UI Sensibility: An eye for clear, effective data storytelling and clean, user-friendly interface design.

• AI Development Environment: Experience with Claude's broader product suite (Artifacts, Claude API, Claude in Chrome) or comparable AI-assisted development environments.

Preferred Skills:

• Python for Data Wrangling: Hands-on experience with Python libraries like Pandas for data manipulation and analysis.

• Legacy BI Migration: Prior experience assisting or leading a team in migrating away from legacy BI tools (e.g., Tableau, Power BI, Looker) towards custom-built tooling.

• Deployment Workflows: Experience with basic deployment workflows using platforms like Vercel, Netlify, or internal hosting solutions.

📝 Enhancement Note: The emphasis on "real code" and specific front-end technologies like JavaScript, TypeScript, and React, alongside AI coding tools, clearly differentiates this role from a traditional BI analyst. The mention of Python is a valuable addition for data wrangling. The preference for experience migrating from legacy BI tools suggests the company is actively looking to innovate its data tooling.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Code-Based Visualizations: Demonstrations of interactive data visualizations built using actual code (JavaScript/TypeScript, React) and visualization libraries.

• AI-Assisted Development: Examples showcasing the use of AI coding agents (like Claude Code) in the development process, highlighting how AI was leveraged to accelerate prototyping or code generation.

• Interactive Web Applications: Prototypes or deployed internal tools that go beyond static dashboards, demonstrating functionality, user interaction, and problem-solving capabilities.

• Data Integration Examples: Evidence of connecting applications or visualizations to live data sources, databases, or APIs.

• Problem-Solving Case Studies: Clear articulation of a business problem, the AI-assisted solution developed, and the resulting impact or value delivered.

Process Documentation:

• Iterative Development: Showcase projects that demonstrate an iterative development process, including initial concepts, feedback loops, and refined final versions.

• Rapid Prototyping: Examples that highlight the speed of development, moving from idea to a functional prototype quickly.

• Stakeholder Collaboration: Evidence of working with stakeholders to define requirements, gather feedback, and deliver solutions that meet their needs.

• Full Lifecycle Ownership: Projects where you managed the complete development cycle, from initial conception and coding to deployment and iteration.

📝 Enhancement Note: Given the unique nature of this role, the portfolio should strongly emphasize projects built with code and ideally showcase the use of AI coding tools. The focus is on demonstrating the ability to build functional applications rapidly, not just analyze data or create static reports. Case studies should highlight the speed and effectiveness of the AI-assisted prototyping approach.

💵 Compensation & Benefits

Salary Range: The competitive salary for this position is between $75,000 to $85,000 USD per year, commensurate with experience and qualifications.

Benefits:

• Comprehensive Medical Insurance

• Dental Insurance

• Vision Insurance

• Life Insurance

• Disability Insurance

• Paid Vacation time

• 401k Retirement Plan

Working Hours: This is a full-time position, typically expected to involve 40 hours per week. While remote candidates may be considered, the role requires dedicated time for collaboration and development, implying a structured work schedule.

📝 Enhancement Note: The salary range is provided and falls within the typical mid-level range for specialized analyst roles in tech hubs in the US. The benefits package is standard for a full-time corporate position, offering good coverage for health and retirement. The explicit mention of "40 hours per week" clarifies expectations for a full-time role.

🎯 Team & Company Context

🏢 Company Culture

Industry: Live Events, Venues, and Brands (Sports, Entertainment, Hospitality). ASM Global, through its Legends Global brand, operates at the intersection of technology, data, and customer experience within the high-stakes live event industry. This context implies a fast-paced, dynamic environment driven by real-time data and a need for innovative solutions.

Company Size: ASM Global is a large global organization with a vast network of 450 venues worldwide, hosting 20,000 events and entertaining 165 million guests annually. This scale suggests a complex operational landscape and significant opportunities for data-driven impact.

Founded: While the founding date for ASM Global isn't explicitly stated, its description as a "premier partner" implies significant history and established operations. The culture described is one of "respect, ambitious thinking, collaboration, and bold action," aiming for an inclusive workplace where employees can be authentic, make an impact, and grow their careers. "Winning is an everyday thing" suggests a performance-oriented, team-driven atmosphere.

Team Structure:

• Insights Department: This role sits within the "Insights" department, reporting to the "Manager, Data & Analytics." This indicates a dedicated team focused on leveraging data to drive business decisions.

• Cross-Functional Collaboration: The role requires close partnership with data engineering and direct interaction with non-technical stakeholders across various business units to understand needs and deliver solutions.

• Agile Development Focus: The team likely operates with an agile mindset, emphasizing rapid iteration, proof-of-concept development, and continuous improvement, especially given the AI-assisted prototyping nature of this role.

Methodology:

• AI-Assisted Development: The core methodology revolves around using AI coding agents (Claude Code) as a primary tool for building applications and visualizations, emphasizing speed and efficiency.

• Data-Driven Decision Making: The ultimate goal is to provide decision-makers with actionable insights through custom-built tools, supporting strategic and operational choices.

• Iterative Product Development: Prototypes are expected to evolve into production-quality tools based on real-world usage and stakeholder feedback, embodying a lean product development approach.

Company Website: https://www.asmglobal.com/

📝 Enhancement Note: The company context highlights a large, established player in the live events industry that is embracing cutting-edge technology like AI for its internal operations. The culture values ambition, collaboration, and impact, which are crucial for an innovative role like this. The "Insights" department structure suggests a mature approach to data utilization.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a mid-level, requiring 2-5 years of experience. It's a specialized position that bridges traditional data analysis with software development, leveraging emerging AI tools. It offers a unique career path for individuals interested in product engineering for data applications rather than pure BI or pure software engineering.

Reporting Structure: The AI Execution & Prototyping Analyst reports to the Manager, Data & Analytics, within the Insights department. This structure suggests mentorship opportunities and a clear line of reporting for performance and project oversight.

Operations Impact: The primary impact of this role is on operational efficiency and decision-making speed. By rapidly creating custom tools and visualizations, the analyst directly empowers stakeholders with timely, relevant data, enabling faster, more informed business decisions across various functions within the live events and venues sector. This role contributes to the company's ability to innovate and maintain a competitive edge through data and AI.

Growth Opportunities:

• AI Development Specialization: Deepen expertise in AI-assisted coding and agentic workflows, potentially becoming a lead in this emerging field within the company.

• Product Engineering Path: Transition into a dedicated product engineering role, focusing on building and scaling internal data applications and tools.

• Data Strategy & Architecture: Grow into roles that influence the broader data strategy, architecture, and technology stack decisions for the Insights department and beyond.

• Leadership Development: With proven success, opportunities may arise to lead projects, mentor junior analysts, or manage a team focused on AI-driven data solutions.

• Cross-Functional Advancement: Leverage deep understanding of business needs gained from stakeholder interaction to move into broader business analysis or operational management roles within the live events industry.

📝 Enhancement Note: This role offers a distinct growth trajectory for individuals interested in the intersection of AI, data, and application development. The opportunity to specialize in "agentic coding" and product engineering for data is a significant career differentiator. The company's scale and industry suggest ample opportunities for advancement across various operational and technical domains.

🌐 Work Environment

Office Type: The position is ideally based in one of ASM Global's primary corporate offices (New York, Texas, Pennsylvania, California, or Illinois). However, remote candidates are also considered, suggesting a flexible work environment that accommodates distributed teams.

Office Location(s): The primary office locations are Frisco, TX; New York, NY; Chicago, IL; West Conshohocken, PA; and Culver City, CA. For remote employees, the expectation is likely to align with a primary time zone or maintain availability during core business hours.

Workspace Context:

• Collaborative & Innovative: The company culture emphasizes collaboration and bold action, suggesting a dynamic workspace that encourages idea-sharing and teamwork, whether in-office or remotely.

• Technology-Rich Environment: As a company embracing AI and custom tooling, expect access to modern development environments, cloud infrastructure, and potentially cutting-edge AI platforms.

• Stakeholder Interaction: The role involves significant interaction with non-technical stakeholders, requiring effective communication and the ability to translate technical concepts into business value within a professional office or remote setting.

Work Schedule: This is a full-time role with standard working hours (approximately 40 hours per week). While remote work is an option, the expectation is for consistent availability and engagement during business hours to facilitate rapid prototyping and stakeholder collaboration.

📝 Enhancement Note: The hybrid/remote flexibility is a key aspect, making the role accessible to a wider talent pool. The emphasis on collaboration and innovation suggests a positive and forward-thinking work environment, whether in-person or virtual.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and portfolio to assess technical skills, relevant experience, and alignment with the role's unique requirements (AI coding, front-end development, data visualization).

• Technical Interview(s): In-depth discussions covering your experience with JavaScript, React, SQL, and your understanding of AI coding tools like Claude Code. Expect coding challenges or live coding exercises focused on data manipulation, visualization, and potentially AI prompt engineering.

• Portfolio Presentation: A dedicated session where you will present 1-2 key projects from your portfolio, highlighting your process, technical decisions, use of AI, and the impact of your work.

• Stakeholder/Manager Interview: Behavioral and situational questions focused on your problem-solving approach, communication skills, ability to work with non-technical users, and cultural fit within the "Insights" team and ASM Global's values.

• Final Round: Potentially a discussion with a senior leader to assess strategic thinking and long-term potential.

Portfolio Review Tips:

• Showcase AI Integration: Clearly highlight projects where you utilized AI coding tools (Claude Code, etc.) and explain the benefits gained (speed, efficiency, complexity handled).

• Code-Centric Examples: Prioritize projects built with actual code (JavaScript/TypeScript, React) over those solely from BI platforms. Include links to live demos or well-documented GitHub repositories.

• Problem-Solution-Impact: For each project, clearly articulate the business problem, the technical solution you developed (especially the AI-assisted aspects), and the tangible impact or value delivered.

• Demonstrate Full Lifecycle: Include projects where you managed the entire development process, from initial concept and stakeholder discussions to deployment and iteration.

• Clarity and Conciseness: Ensure your portfolio is well-organized, easy to navigate, and that your contributions are clearly defined.

Challenge Preparation:

• AI Coding Scenarios: Be prepared to discuss how you would approach common data visualization or internal tool requests using Claude Code, including prompt engineering strategies.

• Front-End Fundamentals: Review core JavaScript, TypeScript, and React concepts, as well as common visualization libraries.

• Data Wrangling & SQL: Practice writing SQL queries and discuss strategies for data transformation using Python (Pandas) or within the AI coding environment.

• Stakeholder Communication: Prepare examples of how you've translated complex business needs into technical requirements and presented technical solutions to non-technical audiences.

📝 Enhancement Note: The interview process emphasizes practical application of AI coding tools and front-end development skills. A strong, code-focused portfolio that demonstrates AI integration and the ability to deliver functional applications is critical for success. The "challenge preparation" section is tailored to the specific tools and methodologies mentioned in the job description.

🛠 Tools & Technology Stack

Primary Tools:

• AI Execution Environment: Anthropic's Claude ecosystem, specifically Claude Code, Artifacts, and MCP-connected tools, will be the primary development environment.

• Front-End Development: JavaScript, TypeScript, React (or similar frameworks) for building user interfaces and interactive components.

• Visualization Libraries: D3.js, Recharts, Plotly.js, Chart.js for creating dynamic charts and graphs.

• Version Control: Git for code management and collaboration.

• Deployment Platforms: Vercel, Netlify, or internal hosting solutions for deploying web applications.

Analytics & Reporting:

• Data Sources: Direct connections to live databases, internal tools, and APIs via MCP.

• Data Wrangling: Python (Pandas) is a plus for data preparation. SQL for querying.

CRM & Automation:

• Integration Protocol: Model Context Protocol (MCP) for connecting AI tools to external systems and APIs.

📝 Enhancement Note: The technology stack is heavily centered around Anthropic's AI tools. Proficiency in modern front-end development (JavaScript, React) and data querying (SQL) is essential, with Python being a beneficial addition. The reliance on MCP for data integration is a key technical requirement.

👥 Team Culture & Values

Operations Values:

• Prototyping Mindset: A strong emphasis on shipping functional versions quickly and iterating based on real usage, valuing speed and iteration over perfection in initial stages.

• Product Engineering Thinking: Approaching data visualization and internal tool development with a product-oriented mindset, considering user needs, scalability, and long-term value.

• Data-Driven Innovation: A commitment to leveraging data and emerging AI technologies to create innovative solutions that drive business impact and replace inefficient legacy systems.

• Collaboration & Bold Action: A culture that encourages teamwork, open communication, and taking initiative to solve problems and drive progress.

• Efficiency & Automation: A focus on building tools that automate processes, enhance efficiency, and provide clear, actionable insights to decision-makers.

Collaboration Style:

• Direct Stakeholder Engagement: Working closely with non-technical stakeholders to understand their needs and deliver tailored solutions.

• Agile Teamwork: Collaborating within the "Insights" team, potentially with data engineers and other analysts, using agile methodologies for rapid development.

• Knowledge Sharing: A culture that likely encourages sharing best practices, code components, and learnings related to AI-assisted development and data visualization.

• Feedback-Driven Improvement: Embracing continuous feedback loops from users and team members to refine tools and processes.

📝 Enhancement Note: The company values align with the innovative and fast-paced nature of the role. A candidate who is comfortable with rapid iteration, proactive problem-solving, and strong collaboration will thrive here. The emphasis on "bold action" suggests a culture that supports experimentation with new technologies like AI.

⚡ Challenges & Growth Opportunities

Challenges:

• Adoption of New Technology: Overcoming potential resistance to new AI-driven workflows and educating stakeholders on the benefits compared to traditional BI tools.

• Rapid Iteration Demands: Managing the expectation for speed and the need to deliver functional prototypes quickly, while ensuring underlying data quality and application stability.

• Balancing Prototype vs. Production: Effectively transitioning validated prototypes into robust, production-grade applications, requiring careful consideration of scalability, security, and maintenance.

• Evolving AI Landscape: Staying current with the rapid advancements in AI coding tools and integrating new capabilities to maintain a competitive edge.

Learning & Development Opportunities:

• AI Expertise: Deepen skills in prompt engineering, AI model interaction, and the application of generative AI for software development.

• Full-Stack Development: Enhance front-end development skills (React, TypeScript) and gain experience with back-end concepts related to data pipelines and application deployment.

• Product Management Fundamentals: Develop a stronger understanding of product lifecycle management, user experience design, and translating business needs into technical specifications.

• Industry-Specific Data Applications: Gain specialized knowledge in data analytics and visualization relevant to the live events, sports, and entertainment industries.

• Mentorship: Opportunities to learn from experienced data professionals and potentially mentor junior colleagues as the team grows.

📝 Enhancement Note: The challenges are directly related to the novelty of the role and the technologies involved. The growth opportunities are significant, offering a chance to become an expert in a cutting-edge field with broad applicability.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you translated a vague business question into a concrete, actionable data visualization or tool. How did you use AI in that process?" (Focus on your iterative approach, stakeholder management, and AI tool usage.)

• "Walk me through a project where you built an interactive web application. What was your development process, what challenges did you face, and how did you overcome them?" (Highlight your coding skills, problem-solving, and ability to take a project from concept to completion.)

• "How would you approach building a real-time attendance tracker for an event venue using Claude Code, connecting to live ticket sales data?" (Demonstrate your understanding of data integration, application logic, and AI-assisted development strategies.) Company & Culture Questions:

• "What excites you about ASM Global and the live events industry, and how do you see data and AI playing a role in it?" (Show your research and genuine interest in the company's domain.)

• "How do you balance the need for rapid prototyping with ensuring the quality and reliability of production applications?" (Address your understanding of agile development and quality assurance.)

• "Describe your experience working with non-technical stakeholders. How do you ensure clear communication and alignment on project goals?" (Showcase your communication and collaboration skills.) Portfolio Presentation Strategy:

• Focus on AI Impact: For each selected project, clearly articulate how Claude Code or other AI tools were used and the specific benefits derived (e.g., reduced development time, enhanced functionality).

• Show, Don't Just Tell: Use live demos where possible, or provide clear screenshots and code snippets to illustrate your work.

• Structure Your Narrative: For each project, follow a clear structure: Problem -> Your Solution (including AI's role) -> Technical Stack -> Outcome/Impact.

• Be Ready for Technical Deep Dives: Prepare to discuss your code, architectural choices, and debugging strategies.

📝 Enhancement Note: Interview preparation should heavily lean on demonstrating practical experience with AI coding tools and front-end development. Candidates should be ready to articulate their thought process for building applications and solving problems using these technologies, with a clear understanding of the company's industry.

📌 Application Steps

To apply for this AI Execution & Prototyping Analyst position:

• Submit your application through the provided Workday portal link.

• Tailor Your Resume: Highlight experience with JavaScript, TypeScript, React, SQL, and any prior use of AI coding assistants or agentic development tools. Quantify achievements where possible, focusing on speed of delivery and impact.

• Curate Your Portfolio: Select 1-2 projects that best showcase your ability to build interactive applications and visualizations using code, with a clear emphasis on any AI-assisted development. Ensure projects are accessible (e.g., live demos, GitHub repos) and well-documented.

• Prepare Your Narrative: Practice articulating your projects, technical decisions, and problem-solving approaches, particularly how you leverage AI tools for rapid prototyping and execution. Be ready to discuss your understanding of the live events industry.

• Research ASM Global: Familiarize yourself with ASM Global's operations, venues, and recent news to demonstrate genuine interest and understand their business context.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.