Data Science and AI Engineer - Southeast Asia & Asia

About the Role

At Chanel's Southeast Asia and Asia (SEAA) division, the focus is on utilizing data to foster sustainable growth, enhance business results, and refine luxury client experiences regionally. The Data Science and AI Engineer is responsible for crafting and implementing AI solutions that turn data into impactful business insights. Spanning areas like CRM, retail, merchandising, marketing, and operations, the role involves building advanced analytics, machine learning models, generative AI, and autonomous AI solutions to boost decision-making, client engagement, workflow automation, and innovation, all while upholding Chanel's high standards of discretion and excellence.

Key Responsibilities

• Design and develop machine learning and statistical models addressing diverse business questions related to client intelligence, CRM, retail metrics, merchandising, marketing, and operational processes.
• Implement techniques such as propensity modeling, recommendation systems, forecasting, classification, clustering, uplift modeling, and anomaly detection to create scalable analytical and ML solutions.
• Process, transform, and engineer large-scale structured and unstructured datasets for modeling, experimentation, and analytics product creation.
• Create reusable data science workflows, feature engineering approaches, model training pipelines, and evaluation frameworks for enhanced scalability and repeatability.
• Collaborate with data engineering and tech teams to ensure data pipelines, model features, and datasets are reliable, properly structured, and production-ready.
• Design and test generative AI solutions incorporating prompt-driven workflows, retrieval-augmented generation, embedding workflows, and applications powered by large language models (LLMs).
• Utilize Python, LLM APIs, LangChain/LangGraph, embeddings, vector search, retrieval-augmented generation (RAG), and tool invocation to build reusable, scalable, and governed AI modules.
• Construct test-and-learn methods, pilots, control group experiments, and impact measurement frameworks to validate recommendations and quantify business outcomes.
• Assist in deploying AI and ML solutions into production and business tools, ensuring continuous monitoring of model accuracy, stability, drift, and impact, and making necessary optimizations.
• Document model assumptions, limitations, performance metrics, and technical details to promote transparency, maintainability, and knowledge sharing.
• Ensure responsible AI development and deployment by focusing on data privacy, explainability, model risk, security, and governance.
• Stay updated on emerging data science, generative AI, and AI technologies, assessing and incorporating relevant innovations to improve methodologies and delivery processes.
• Engage with business stakeholders to translate complex analytic outputs into actionable insights and clear visual communication.

Qualifications and Skills

• Proven hands-on experience building machine learning solutions that resolve business challenges.
• Advanced proficiency in Python and associated data science libraries; experience with deep learning frameworks like PyTorch or TensorFlow.
• Familiarity with containerization (Docker), orchestration platforms (Kubernetes), version control (Git), and managing model lifecycle including deployment, monitoring, and retraining.
• Experience with generative AI methods including prompt engineering, RAG pipelines, embeddings, vector databases, semantic search, or text analytics is beneficial.
• Strong expertise with cloud AI/ML platforms such as Databricks, AWS SageMaker, or Azure Machine Learning to lead scalable model development and deployment.
• Exposure to enterprise GenAI tools like Azure AI Foundry, LangChain, or LangGraph preferred.
• Comfort designing experiments including pilots, A/B testing, and control groups to measure and validate analytical impact.
• Understanding of Responsible AI principles addressing privacy, explainability, bias mitigation, hallucination risk, human oversight, and governance controls.
• Experience integrating AI-assisted coding tools (e.g., Cursor, GitHub Copilot, Claude Code) within development workflows.
• Strong adaptability and eagerness to keep pace with fast AI advances, applying emergent capabilities to practical enterprise challenges.
• Good communication skills to effectively liaise with business users, translating complex technical concepts into clear and actionable insights.

Success Indicators

• Delivery of AI and data science solutions that generate quantifiable business value and enhance decision quality.
• Deployment of models demonstrate stable, reliable, and explainable performance consistent with agreed expectations.
• Effective identification and prioritization of high-impact use cases with executable project plans.
• Integration of analytics and AI outputs into business tools, dashboards, and workflows widely adopted by users.
• Reuse of modeling assets and AI components accelerates future analytics and AI solution delivery.
• Positive stakeholder feedback confirming solution usefulness, transparency, and impact.
• Adherence to Responsible AI and compliance standards ensuring no critical issues related to model misuse or data governance.

Work Environment and Culture

Chanel prioritizes an inclusive workplace that supports personal and collective growth. The company values diverse perspectives and encourages all qualified candidates to apply, acknowledging the important contributions brought by each individual’s unique experience and potential.