Data Specialist - Consumer Product Division
L'Oréal
Job Overview
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Job Description
About L'Oréal
Join L’Oréal, the #1 beauty company globally with a legacy of over 100 years, operating in 150+ markets. We innovate with data, technology, science, and a commitment to inclusivity and sustainability.
Who We Are
Within the Consumers Products Division, our mission is to democratize beauty by delivering top products in haircare, skincare, makeup, and personal care. We integrate scientific research, consumer insights, and advanced technology to strengthen our e-commerce presence and drive revenue growth.
A Day in the Life of the Data Specialist - Consumer Product Division
This role focuses on Revenue Growth Management (RGM) through:
- Data Acquisition, Cleaning & Preparation: Collaborating with IT and RGM teams to collect and validate internal and external data.
- Advanced Analytics & Insight Generation: Performing deep statistical analysis, identifying trends, and quantifying financial impacts.
- Predictive & Prescriptive Model Development: Building forecasting, price elasticity, promotion effectiveness, and product mix models.
- Experimentation and Collaboration: Designing A/B tests and working cross-functionally to translate findings into strategy.
- Continuous Improvement: Staying updated with data science trends and enhancing model performance.
Who You Are
- University graduate with at least 5 years’ experience in beauty or FMCG.
- Fluent in both Korean and English.
- Proficient in MS PPT, Excel, and Word.
Key Skills/Competency
- Data Acquisition
- Data Cleaning
- ETL
- Predictive Modeling
- Statistical Analysis
- Revenue Growth Management
- Advanced Analytics
- Machine Learning
- Model Optimization
- A/B Testing
How to Get Hired at L'Oréal
- Research L'Oréal's culture: Understand the company's global impact and innovation.
- Customize your resume: Highlight data science and RGM experience.
- Showcase relevant skills: Emphasize ETL, modeling, and analytics proficiency.
- Prepare for technical interviews: Brush up on statistical analysis and predictive modeling techniques.
- Follow application guidelines: Include an updated English resume as requested.
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