Role Title: Head of Data & Analytics

Corporate Location: Ho Chi Minh City, Vietnam 

Mission: Lead L’Oréal Vietnam’s Corporate Data & Analytics function. Define the data vision, build scalable platforms, and deliver trusted insights that elevate decision-making across corporate domains (Commercial, Marketing, Market Research, Social, Digital, Supply Chain. Finance).

You will run data as a product and as a business, balancing near-term value with long-term capability building.

What You’ll Do:

Strategy, Governance & Risk

· Set and execute the corporate data strategy aligned with L’Oréal Group guidelines and Vietnam market priorities.

· Establish data ownership, stewardship, quality standards, and policies; define enterprise KPIs and shared data definitions.

· Ensure compliance with privacy and security regulations and internal information security standards.

Leadership, Change & Value Realization

· Lead, coach, and develop a team of data specialists (data engineers, data analysts, analytics product owners, data scientist).

· Drive adoption through stakeholder enablement, training, and change management; embed “data as a product” and self-service analytics.

· Own the portfolio and roadmap; prioritize by ROI and strategic impact, track OKRs, and report value realization.

· Partner with Corporate leaders to translate business needs into data products, insights, and automation opportunities.

Analytics, BI & Data Science

· Own the cloud-first data architecture and data platform (e.g: lakehouse, pipelines, metadata, observability, lineage).

· Deliver executive-ready dashboards, KPI frameworks, and narratives that enable decisions across functions.

· Lead advanced analytics and GenAI (e.g., demand planning, spend optimization, risk/compliance analytics, social metrics).

· Translate complex findings into clear recommendations and action plans for senior stakeholders.

What You Bring

· Data Strategy & Governance: Proven experience setting strategy, operating models, and policies; data quality and stewardship; KPI harmonization.

· Data Architecture & Engineering: Strong knowledge of cloud-first architectures (e.g., Azure/AWS/GCP), data modeling, ETL/ELT, APIs, MDM, metadata/lineage.

· Advanced Analytics & Data Science: Hands-on or leadership experience in predictive modeling, forecasting, optimization, and experimentation; familiarity with MLOps.

· Business Intelligence & Storytelling: Track record building executive dashboards and converting analytics into decisions; exceptional data storytelling.

· Leadership & Influence: Excellent stakeholder management across Finance//Commercial/IT/Supply Chain; ability to prioritize, negotiate trade-offs, and lead change end to end.

· Compliance & Security: Understanding of data privacy, security, responsible AI, and model risk management.

· Experience in consumer goods/retail or E-commerce environments.

· Exposure to GenAI use cases, prompt governance, and enterprise-grade deployment patterns.

· Tools familiarity: GCP, Big Query, dbt, Airflow, Power BI, Python, SQL.