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About the Role
We are seeking a hands-on Advanced Analytics & Data Enablement Analyst to transform Korean business data into actionable insights and measurable value. This role acts as a strategic business partner, translating business, media, digital, and market questions into tailored analytical solutions and recommendations. The ideal candidate is curious, analytically rigorous, and commercially minded, investigating root causes and challenging assumptions to drive understanding of business performance.
Responsibilities
- Translate business questions into structured analytical hypotheses, data requirements, analytical approaches, intended business actions, and success measures.
- Select solutions based on business value, reliability, interpretability, scalability, feasibility, and adoption potential.
- Apply appropriate model-validation methods, baseline comparisons, and performance metrics.
- Document analytical methods, assumptions, limitations, outputs, and recommendations clearly.
- Challenge stakeholder assumptions and validate whether observed patterns are genuine insights, data artefacts, process changes, or temporary effects.
- Develop and test multiple hypotheses and solution options.
- Adapt analytical approaches when data, findings, or business requirements indicate a more effective solution.
- Communicate uncertainty, data limitations, risks, and the strength of evidence transparently.
- Assess data fitness for purpose before use in reporting, analytics, activation, machine learning, or AI.
- Identify data-quality issues such as missing or duplicate records, inconsistent definitions, unreliable joins, incomplete histories, late-arriving data, source-system changes, and potential bias.
- Support fit-for-purpose data governance for analytics use cases, including business definitions, data ownership, source documentation, lineage awareness, data-quality checks, and appropriate data use.
- Understand and apply relevant privacy, consent, access-control, and responsible-data-use requirements.
- Build reproducible, well-organized, and documented analytical workflows.
- Escalate early when data is not sufficiently reliable or appropriate for a business decision, activation, dashboard, model, or AI use case.
- Stay informed about relevant analytics, AI, automation, data-visualization, and data-platform technologies.
- Conduct focused proofs of concept to evaluate emerging tools and methods.
- Contribute to a culture of experimentation, knowledge sharing, continuous learning, analytics best practices, and evidence-based decision-making.
- Support the upskilling of business stakeholders by helping teams understand, interpret, and act on analytical insights effectively.
- Work closely with the Project Manager, providing technical input into project scope, data dependencies, risks, effort estimates, solution options, and delivery plans.
- Participate in stakeholder discussions to clarify questions, validate assumptions, and explain analytical findings.
- Partner effectively with local and regional data, CRM, digital, media, tech, retail, commercial, and business teams.
- Leverage relevant advanced models and regional capabilities to support local business operations and decision-making.
- Assess regional data, analytics, CRM, and AI capabilities for Korea business relevance, data readiness, local process fit, and value potential.
- Support local testing, user acceptance testing, adoption feedback, and enhancement requests for relevant regional capabilities.
- Demonstrate a hands-on ownership mindset: proactively investigate issues, propose solutions, and help remove barriers to delivery.
- Know when to involve subject-matter experts or escalate structural data, technology, privacy, security, or process risks.
- Build, improve, or validate priority advanced analytics or applied ML use cases with defined business value.
- Produce activation-ready outputs that can support CRM, campaign, media, retail, clienteling, digital, e-commerce, or commercial actions.
- Establish disciplined practices for data validation, KPI documentation, analytical documentation, and reproducible work.
- Identify critical data-definition, data-quality, consent, access, or data-structure issues early and mobilize the appropriate owners to address them.
- Help strengthen Korea’s capability to move from reporting what happened to understanding why it happened, what is likely to happen, what action to take, and how to measure the outcome.
- Actively contribute to data governance, quality, KPI standards, analytical reliability, and responsible AI practices for analytics and activation use cases.
Requirements
- Bachelor’s degree or equivalent practical experience in Data Science, Statistics, Mathematics, Computer Science, Engineering, Business Analytics, or another quantitative discipline.
- Relevant experience in advanced analytics, data science, CRM/customer analytics, digital analytics, commercial analytics, business intelligence, consulting, or a similar data-focused role.
- Strong SQL skills and confidence working with complex, large, and imperfect data sets from multiple sources.
- Proficiency in Python for data analysis, statistical modeling, and machine learning.
- Practical experience in one or more of the following: Predictive modeling or classification, Customer segmentation or clustering, Propensity, churn, customer-value, or next-best-action modeling, Anomaly detection, Recommendation or personalization, generative AI, or analytics automation.
- Understanding of key model-development concepts, including feature engineering, train/test validation, baseline comparison, performance metrics, overfitting, data leakage, interpretability, and bias.
- Demonstrated ability to conduct deep analysis, formulate hypotheses, validate findings, and develop evidence-based recommendations.
- Familiarity with core data-governance concepts, including data quality, business definitions, data ownership, data lineage, access controls, and responsible data use.
- Ability to communicate analytical methods, findings, recommendations, and limitations clearly to technical and non-technical colleagues.
- Experience activating analytical outputs in CRM, marketing, clienteling, retail, digital, commercial, or planning processes.
- Experience operationalizing analytical solutions into recurring workflows, customer journeys, or decision tools.
- Experience with cloud data or analytics environments such as Azure, AWS, GCP, Databricks, Snowflake, or equivalent.
- Familiarity with Git, version control, reusable code, code review, or reproducible analytical workflows.
- Exposure to MLOps, model monitoring, data pipelines, APIs, or deployment practices.
- Familiarity with data catalog, data-quality, or data-governance tools.
- Understanding of privacy, consent, and responsible-AI considerations when working with customer data.
- Evidence of self-directed learning, proof-of-concept development, automation, or adoption of new analytical technologies.
Skills
- Advanced Analytics
- Data Enablement
- Machine Learning
- SQL
- Python
- Data Analysis
- Statistical Modeling
- Predictive Modeling
- Classification
- Customer Segmentation
- Clustering
- Propensity Modeling
- Churn Modeling
- Customer Value Modeling
- Next-Best-Action Modeling
- Anomaly Detection
- Recommendation Systems
- Personalization
- Generative AI
- Analytics Automation
- Data Governance
- Data Quality
- Business Intelligence
- CRM Analytics
- Digital Analytics
- Commercial Analytics
- Cloud Data Environments (Azure, AWS, GCP, Databricks, Snowflake)
- Git
- Version Control
- MLOps
- Model Monitoring
- Data Pipelines
- APIs
- Responsible AI
Location
- Korea
Work Type
- Full-time
Experience Level
- Advanced
Education Level
- Bachelor's degree or equivalent practical experience
About the Company
- CHANEL is a privately-owned company focused on creating an environment where employees can perform at their best and feel fulfilled and confident.
- The company values employee humanity and uniqueness, striving to create a safe environment where individuals can bring their full selves to work.
- Inspired by Gabrielle Chanel, the company encourages a unique work environment that fosters personal and professional growth.
- CHANEL is committed to being a purposeful and human-driven employer, fostering inclusion, collaboration, and well-being for long-term business success.