AI Automation & Growth Analyst

AI Automation & Growth Analyst

At Warner Chappell Music (WCM) - the global music publishing arm of Warner Music Group (WMG) - we shape the culture of songwriting and champion songs that resonate for generations by creating transformational opportunities for songwriters everywhere. Our people and culture are at the epicenter of our company, and we are looking for team members who share our service-oriented mindset and have a passion for looking after our songwriters.

The AI Automation & Growth Analyst reports to the Senior Manager, Data Analytics & Automation within the Strategy, Integration and Operations Department and is located in Los Angeles.

Your Role

The AI Automation & Growth Analyst is the technical engine behind our team's ability to scale. You will own the end-to-end lifecycle of automation solutions—from identifying bottlenecks in manual workflows to designing and deploying robust, code-based solutions.

In this role, you will move beyond simple prompting; you will use Python or JavaScript, SQL, and LLM APIs to build intelligent pipelines that streamline complex workflows. Your primary objective is to enhance data-driven decision-making and operational efficiency by treating automation as a software engineering discipline.

What You'll Do

• Engineer Robust Automations: Design and script automated workflows using Python or JavaScript to replace manual, data-intensive tasks across our departments.
• Build AI-Integrated Data Pipelines: Write complex SQL queries to extract and transform data, then integrate that data with Large Language Models (LLMs) to generate automated outputs.
• Develop Intelligent Applications: Engage in the full development lifecycle to build internal tools and agents using custom logic and direct API integrations.
• Maintain Engineering Standards: Utilize Git for version control, conducting code reviews, and ensuring all automation scripts are documented, tested, and reliable.
• Drive Rapid Prototyping: Utilize AI-assisted coding tools (e.g., Cursor, Windsurf) to accelerate the creation of business-focused applications while maintaining clean code architecture.
• Analyze & Optimize Processes: Create process maps to deconstruct current business operations, identifying specific nodes where AI agents or scripts can improve speed and accuracy.
• Full-Stack Contribution: Contribute to backend logic (API integrations, database management) and simple user-facing interfaces to make your tools accessible to non-technical colleagues.
• Develop Deep Expertise in Applied AI: Grow into a subject-matter expert by researching, experimenting with, and applying emerging AI technologies to practical business use cases.
• Collaborate to Drive Innovation: Work in a tight-knit team and partner with business stakeholders to champion new ideas, ensure smooth project execution, and encourage the adoption of new technologies.
• Learn and grow: Actively participate in training and development opportunities to enhance skills in AI, automation technologies, and process improvement methodologies.

About You

We are looking for an early career-level AI Automation & Growth Analyst with an obsessive drive for learning and staying at the forefront of AI and automation advancements. With a background in software engineering (or related), the ideal candidate will be deeply passionate about exploring the latest technologies and immersing themselves in this rapidly evolving field. A keen interest in AI trends and a proactive approach to discovering new tools and solutions will be essential. This role is perfect for someone who thrives on continuous learning and staying ahead of emerging technologies in AI.

Desired Skills & Experience

• Strong Scripting Skills (Python or JavaScript): Hands-on experience using Python or JavaScript/TypeScript for data manipulation, API interaction, and process automation; preference for scripting over manual tasks.
• Data & SQL Fluency: Comfortable writing SQL queries to pull, clean, and structure data from relational databases, understanding data preparation for AI context windows.
• Version Control (Git): Familiarity with branching, merging, and pull requests to maintain a clean codebase in a team environment.
• LLM & API Experience: Built applications or scripts utilizing LLM APIs (OpenAI, Anthropic, Gemini), understanding concepts like context limits, temperature, and prompt engineering.
• Grounded in Engineering Principles: Strives to write clean, scalable, and reliable code that can be maintained and built upon by the team.
• Obsessive Drive for AI: Goes beyond coursework, constantly exploring latest technologies, building personal projects, and experimenting with agentic workflows.
• Product-Minded & Pragmatic: Independently translates business needs into technical solutions with a