Our Data & AI Vision
We are building an AI-native data platform that:
- Unifies data across ecommerce, marketing, creators, and operations into a real-time, governed data foundation
- Moves beyond dashboards to deliver proactive, predictive, and prescriptive insights
- Enables AI-driven self-serve analytics for business users via natural language, copilots, and agents
- Powers autonomous decision-making and optimization across pricing, campaigns, inventory, and content
- Embeds machine learning and generative AI into core workflows (forecasting, recommendations, anomaly detection, content insights)
- Acts as the intelligence backbone of our internal tech platforms
Our current stack includes Google BigQuery, StarRocks, Airflow, DBT, Cube.dev (semantic layer), Looker Studio, and Apache Superset—and we are evolving this into a modern AI + data platform with real-time, ML, and agentic capabilities.
Role Overview
We are looking for a hands-on Head of Data & Analytics to lead the transformation from a traditional BI and data platform into an AI-driven intelligence platform.
You will:
- Own the end-to-end data, analytics, and AI strategy
- Build a platform that shifts the company from reporting → insights → actions → autonomous optimization
- Enable both internal teams and external clients with self-serve, AI-powered decision-making tools
- Partner closely with Product, Engineering, and Business teams to embed intelligence into every workflow
This role requires someone who is equally comfortable:
- Defining data + AI strategy at the leadership level
- Designing modern data and ML architectures
- Driving real business impact through insights and automation
Key Responsibilities
1. Data, Analytics & AI Strategy
- Define and execute the roadmap for an AI-native data platform aligned with Intrepid’s product and business strategy
- Evolve the organization from dashboarding → proactive insights → autonomous intelligence systems
- Identify and prioritize high-impact opportunities across ML, GenAI, and agentic workflows in ecommerce, marketing, and social commerce
- Drive adoption of AI-powered self-serve analytics and copilots across business teams
2. Data Platform, Architecture & Governance
- Own the design and evolution of the modern data stack, including:
- Data warehouse/lakehouse (BigQuery, StarRocks)
- Data pipelines (Airflow, DBT)
- Semantic layer (Cube.dev)
- BI tools (Looker Studio, Superset)
- Extend the platform to support:
- Real-time and streaming data use cases for social commerce
- Vector databases, MCP, and LLM integration layers
- Establish strong foundations for data governance, privacy, security, quality, lineage, and cataloging
- Ensure platform scalability, reliability, and cost efficiency
3. AI, Machine Learning & Intelligent Systems
- Lead the development and deployment of:
- Anomaly detection and automated insight systems
- Generative AI use cases (copilots, automated reporting, content insights)
- Recommendation systems (product, pricing, targeting)
- Predictive models (forecasting, ROAS optimization, churn, inventory planning)
- Drive adoption of LLM-powered analytics (NL2SQL, conversational BI, insight generation)
- Build foundations for agentic AI systems that can autonomously analyze, recommend, and act
4. Business Impact, Self-Serve & Team Leadership
- Transition from pull-based dashboards → push-based, actionable insights
- Enable business teams with:
- Proactive alerts, recommendations, and decision support tools
- Scenario simulation and planning capabilities
- Build AI-powered self-serve analytics experiences, reducing dependency on central teams
- Drive semantic layer adoption and metrics standardization across the organization
- Define and track impact metrics (e.g., GMV uplift, marketing efficiency, cost reduction, automation rates)
- Build and lead a high-performing data organization (Data Engineering, Analytics Engineering, Data Science, BI)
Foster a culture of ownership, experimentation, and AI-first thinking, partnering closely with tech and business functions
Experience & Domain Expertise
- 10+ years in data, analytics, and AI roles, with 3+ years in leadership
- Strong experience in ecommerce, marketplaces, martech, or digital platforms
- Proven track record building modern data platforms and scaling data teams
- Experience working in multi-country / SEA environments is a strong plus
AI & Data Expertise
- Deep expertise in the modern data stack:
- BigQuery, DBT, Airflow, real-time pipelines, semantic layers
- Hands-on experience with:
- Generative AI / LLMs (RAG, copilots, natural language interfaces)
- Experimentation frameworks and causal inference
- Machine learning (forecasting, optimization, recommendations)
- Familiarity with:
- Feature stores, MLOps, vector databases, and AI orchestration frameworks
- Strong understanding of data modeling, governance, and scalable architecture
Leadership & Ways of Working
- Proven ability to build and lead multi-disciplinary data teams
- Strong communication skills; able to translate complex data/AI concepts into business value
- Highly analytical and structured thinker
- Comfortable operating in fast-paced, ambiguous, high-growth environments
- Collaborative, pragmatic, and outcome-driven
