Lead Data Scientist, Applied AI, SEAA,

At Chanel SEAA, we aim to leverage data to power sustainable growth, improve business performance and elevate luxury client experiences across the region.

Why This Mission:

CHANEL SEAA is accelerating its data roadmap to expand from business intelligence towards decision intelligence: moving beyond reporting what happened to diagnosing issues, anticipating change and enabling confident, timely action for the brand, clients and business.

The Lead Data Scientist, Applied AI is SEAA’s senior technical authority for data science, machine learning and applied AI. The role turns complex business opportunities into analytically rigorous, scalable and responsible intelligence products that strengthen client understanding, business performance, foresight, judgement and action. This is a player-coach role for someone who combines deep technical credibility with commercial judgement, remains hands-on in priority work, and can influence how leaders understand and act on evidence.

Working across Southeast Asia and Australia, the role partners with business leaders, Insight & Foresight, Data Platform and Engineering, Data Products and Stewardship, Data & AI Enablement, Technology, Global teams and specialist partners. The role adapts its approach to different market contexts and levels of data maturity, while developing solutions that can scale across the region.

Impact You Can Create In The Role:

Lead the Data Science and Applied AI Practice

Set technical direction, standards and leading practices across data science, machine learning, GenAI and agentic AI

Remain hands-on in priority work through problem framing, exploratory analysis, methodological design, prototyping, and code or model review

Guide practitioners and partners, uphold technical quality, transfer knowledge and help shape the future regional data science and applied AI capability

Turn Questions into Decision Intelligence

Partner with business leaders to identify the decisions that matter and define the expected client, boutique, brand, operational or financial value

Choose the simplest robust method, challenging whether AI is the right response

Connect internal client and business evidence with external market, cultural and industry signals in partnership with Insight & Foresight

Synthesise evidence into clear implications, uncertainties, trade-offs and recommended action

Build and Scale Advanced Analytics and Applied AI

Lead the design and validation of statistical, machine-learning, GenAI and agentic solutions for priority use case

Establish rigorous baselines, evaluation methods, assumptions and limitations

Work with engineering and Technology teams to productionise, monitor and improve solutions on governed, scalable foundations

Create reusable methods, assets and AI components that accelerate delivery and reduce duplication

Drive Adoption and Organisational Shift

Turn complex analysis into compelling, decision-focused stories for executive, market and functional audiences

Champion the shift from retrospective reporting towards diagnosis, foresight, judgement and proactive action

Embed intelligence into business rhythms and use adoption, feedback and outcomes to improve, scale, pause or retire solutions

Responsible AI and Continuous Improvement:

Ensure AI and data science solutions are developed and used responsibly, with appropriate attention to data privacy, explainability, model risk, security and governance

Stay close to emerging data science, GenAI and AI capabilities, assess relevance for Chanel use cases and continuously improve methods, components and delivery practices

The Profile We Are Looking For

Strong technical judgement, with the depth to challenge methods and identify weak assumptions

A hands-on mindset, with the willingness to work directly on priority use cases

Commercial and brand judgement, focused on decisions that matter for clients, boutiques and business performance

Clear and influential communication, turning complex evidence into a point of view and recommended action

A collaborative leadership style, raising the capability of colleagues and partners rather than becoming the sole expert

Your Success Measures

Business and Brand Value: Priority solutions improve decision quality, client experience, growth, operational effectiveness or productivity

Adoption and Decision Impact: Trusted intelligence is embedded in relevant business routines, products and workflow

Analytical Quality and Reliability: Solutions meet agreed standards for validity, performance, explainability, usability and documentation

Speed to Value and Reuse: Reusable methods, assets and components accelerate future delivery

Capability Maturity: Practitioners and partners demonstrate stronger technical practice and increasing independence

Responsible AI: Solutions operate with appropriate oversight and controls, with no critical privacy, security or misuse incidents

Organisational Shift: Leaders increasingly connect internal and external intelligence and move from reporting towards foresight, judgement and action

You are Energised by

Helping shape the future of an iconic House, using data and AI to strengthen CHANEL’s singularity and enduring desirability

Deepening our understanding of clients, uncovering human truths and emerging possibilities that enable CHANEL to create meaningful, memorable experiences

Turning intelligence into imagination and action, helping the organisation see what others do not and make choices that set the standard for luxury

Pioneering responsible applications of AI, bringing together scientific rigour, creativity and human judgement in a way that feels distinctly CHANEL

Building a capability people are proud to create together, inspiring confidence, curiosity and new ways of thinking across the region

What You Will Bring: Capability Requirements

Data Science and Applied AI

At least 7 years of experience in data science and machine learning, including recent hands-on delivery of complex analytical solutions. Practical experience applying GenAI or agentic AI in enterprise settings is strongly preferred

Deep practical expertise in statistical modelling, machine learning, experimentation and model evaluation, with expert Python proficiency

Hands-on experience with enterprise GenAI, including RAG, embeddings, vector search, semantic search and agentic workflows

Recent direct contribution to data-science or applied-AI work, not only programme sponsorship, vendor oversight or people management

Technical Leadership and Production Fluency

Experience setting standards, reviewing technical work, mentoring practitioners and guiding partner delivery teams

Understanding of cloud AI and machine-learning platforms, model lifecycle and MLOps/LLMOps

Ability to partner with engineering teams on deployment, monitoring and lifecycle management without duplicating platform ownership

Business Problem Framing and Influence

Work with business and product partners to translate priority business questions into clear data-science and AI problems

Recommend the right analytical or AI approach, based on value, feasibility and technical rigour

Explain technical choices, assumptions, limitations and results clearly to non-technical stakeholders

Influence decisions through evidence and technical judgement, without taking ownership of business strategy or insight generation

Partner with Insight & Foresight on external signals, and with Data & AI Enablement on adoption and change

Responsible AI and Learning Agility

Strong understanding of privacy, security, explainability, bias, hallucination risk, human oversight and proportionate governance

Disciplined curiosity to assess fast-evolving capabilities and convert relevant advances into practical, governed solutions

At Chanel, we are focused on creating an inclusive culture that nurtures personal growth, con