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

Compensation and Benefits

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