Senior Director, Data Analytics and Artificial Intelligence

True Classic is hiring a Director, Data Analytics and Artificial Intelligence to take ownership of the company’s data, analytics, and AI decision layer. This role will lead the data architecture, infrastructure, reporting intelligence, and AI capabilities that enable every person and agent across the company to access accurate, timely, cost-effective, and actionable insights. This role is ideal for someone who is hands‑on, technically deep, strategic, and AI‑native and can build scalable data platforms, establish trusted analytical systems, develop agentic workflows, and lead high‑performing technical teams in a fast‑paced, evolving environment. All of True Classic’s roles are global and omni‑channel, leading designated areas of accountability across all product categories, countries, and sales and marketing channels. This role will have impact across DTC, retail, wholesale, marketplaces, and emerging channels, ensuring strategic alignment and executional rigor across the enterprise. Areas of Accountability Data Platform and Pipelines Design, operate, and continuously improve the Google BigQuery warehouse for performance, reliability, scalability, and cost efficiency Own the ingestion layer end to end, from source connectors through extraction and load pipelines Establish monitoring, alerting, and clear data contracts across the platform Set standards for orchestration, testing, deployment, documentation, and data quality Data Models, Semantics, and Analytics Lead the development of clean, layered, documented, tested, and maintainable data models using Daasity, dbt, and related technologies Build and govern the semantic layer so company metrics are defined consistently across departments and can be accurately understood by both people and AI agents Deliver and continuously improve the Omni reporting layer, enabling teams to answer their own questions without relying on a centralized reporting queue Establish the metrics, definitions, governance, and change‑management practices required to make self‑service analytics trustworthy Artificial Intelligence and Agentic Systems Lead the in‑house AI team in building applications that democratize access to the information contained within True Classic’s data Design systems that turn business questions into clear insights, specific recommendations, decisions, actions, and ongoing learning loops Enable agentic capabilities across the organization, giving teams AI systems that operate on trusted data with clear permissions governing what agents may read, write, recommend, or decide independently Champion automated workflows that capture data, model information, identify what is happening, recommend action, facilitate decisions, execute work, and feed outcomes back into the system Trust, Cost, and Team Leadership Establish measurable standards for data freshness, accuracy, reliability, and ownership, with clear accountability when performance falls below expectations Develop evaluation frameworks for AI outputs so systems are tested for accuracy and reliability before influencing business decisions Own platform costs across the warehouse, analytics, application, and model layers, continuously improving the value of insight produced per dollar spent Build, hire, mentor, and lead a team of data engineers, analytics engineers, analysts, and AI engineers while setting the technical vision and roadmap for the function Cross‑Functional Collaboration Partner with business and functional leaders to translate ambiguous questions into clear, measurable insights and actionable recommendations Work with AI engineers embedded within Merchandising, Marketing, Operations, Finance, and Customer Experience to ensure departmental workflows are built on shared data, technical, and governance standards Collaborate across Technology, Finance, Merchandising, Marketing, Operations, Customer Experience, and other business teams to ensure company metrics are consistently defined, trusted, accessible, and actionable Qualifications Significant experience in data architecture, data engineering, pipeline engineering, dimensional modeling, semantic modeling, analytics, and artificial intelligence Experience with modern cloud data warehouses, ideally Google BigQuery, as well as strong SQL and reliable, cost‑conscious data pipelines Strong technical and analytical skills, including experience building documented, tested, version‑controlled, and maintainable data models Ability to design and deliver self‑service analytics, reporting systems, applications, AI tools, and automated decision workflows Demonstrated ability to lead and grow technical teams, establish a technical roadmap, manage complex systems, and determine when to build versus buy Preferred Qualifications Experience with Google BigQuery, Daasity, dbt, Omni, Supabase, Vercel, Claude Code, Claude Design, Codex, GitHub, Google Workspace, and SSO Experience working within ecommerce, retail, or an omni‑channel consumer brand Familiarity with business systems including Shopify, Amazon, NetSuite, Ramp, ShipBob, Stord, and other ecommerce, finance, and third‑party logistics platforms Demonstrated experience building a data or AI platform from the ground up or supporting demand planning, forecasting, inventory, or other commercially significant business functions Workplace Arrangement This role is on‑site, five days a week, based in Calabasas, California. Compensation and Benefits Compensation Competitive salary Performance bonus 401(k) plan with 3% company match Time Off Unlimited PTO and sick time Health and Wellness Company-paid medical, dental, and vision insurance $100 per month Health and Wellness stipend Free Employee Assistance Program Work and Growth Support $100 per month Personal Workspace/Office stipend Perks $1,000 per year True Classic merchandise allowance #J-18808-Ljbffr True Classic