Job Title: Manager, Data Science, CPD Advanced Analytics
Department: One L'Oréal Data
Reports To: AVP, Analytics Lead – Advanced Analytics
Who We Are:
For more than a century, L'Oréal has devoted its energy, innovation, and scientific excellence solely to one business: Beauty. Our goal is to offer each and every person around the world the best of beauty in terms of quality, efficacy, safety, sincerity and responsibility to satisfy all beauty needs and desires in their infinite diversity.
At L'Oréal, our One L'Oréal Data organization mission is to enable data at the speed of beauty and drive sustainable growth. We translate insights into action to deliver value for L'Oréal, our consumers, and the planet. We empower each other through data, insights, & agility, preparing L'Oréal for the future of a data driven world. Come join our dynamic team!
About Our Team:
The CPD (Consumer Product Division) Advanced Analytics team tackles critical challenges through statistical modeling, forecasting, and AI innovation (including agentic AI) to drive smarter decisions across L'Oréal.
About the Role:
As a Manager, Data Science on the CPD Advanced Analytics team, you'll be a modeling expert driving critical decisions across our organization. You'll build sophisticated statistical and machine learning models that solve our most challenging analytical problems, from sales forecasting that accounts for seasonality, promotions, and pricing dynamics, to predictive models for new product launches, marketing mix models for media attribution, and advanced analytics leveraging consumer sentiment and behavioral data. Your work will directly influence inventory planning, pricing strategy, product launches, and promotional effectiveness at the highest levels. This is an individual contributor role for a passionate modeler who wants to deliver measurable impact.
You'll Thrive in This Role If:
- You've built production models that influenced real business decisions, not just academic exercises
- You're versatile in your modeling approach, whether it's time series forecasting, marketing mix modeling, or extracting insights from text data, you pick the right tool for the business problem
- You can explain complex statistical concepts to executives and make them care about the insights
- You thrive on solving messy, ambiguous problems where the right answer isn't obvious
- You're equally comfortable writing Python code, debugging a model, and presenting to senior leadership
Key Responsibilities:
DATA EXPLORATION & PREPARATION
- Gather and integrate data from sales systems, promotional calendars, pricing databases, product attributes, consumer feedback, media spend, and external market sources
- Develop deep understanding of key drivers including promotional mechanics, pricing strategies, product lifecycles, seasonal trends, and consumer behavior
ADVANCED MODELING & ANALYTICS
- Build production-grade sales forecasting models that incorporate seasonality, promotional effects, pricing dynamics, and holiday impacts
- Develop predictive models including attribute-based launch forecasts, marketing mix models for media attribution, and consumer analytics leveraging text, sentiment, or behavioral data
- Apply advanced statistical and machine learning techniques including time series analysis, regression modeling, causal inference, ensemble methods, and NLP/text mining
- Ensure statistical rigor through backtesting, sensitivity analysis, and performance validation (with growth into deep learning approaches)
MODEL DEPLOYMENT & OPERATIONS
- Deploy models to production on Google Cloud Platform with focus on scalability and reliability
- Monitor performance over time, diagnose degradation, and implement governance practices including documentation, version control, and reproducibility
STAKEHOLDER PARTNERSHIP & COMMUNICATION
- Partner with Finance, Marketing, Sales, and Supply Chain to understand challenges and frame analytical solutions
- Translate complex statistical concepts into clear, actionable insights for non-technical executives and present findings to senior leadership
- Build trusted relationships with stakeholders through consistent delivery and domain expertise
What You'll Bring:
Required:
- Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Data Science, or related quantitative field
- 3-5+ years building and deploying statistical and machine learning models in production
- Strong foundation in statistical modeling and advanced analytics with expertise in multiple techniques (forecasting, regression, classification, causal inference, or experimental design)
- Advanced proficiency in Python (pandas, scikit-learn, statsmodels) and SQL
- Proven track record translating analytical problems into statistically sound, actionable solutions
- Excellent communication skills with ability to explain technical concepts and influence decision-making
Preferred:
- Master's or PhD in Statistics, Mathematics, Computer Science, Economics, or Operations Research
- Deep expertise in forecasting methodologies including time series analysis (ARIMA, SARIMA, Prophet, LSTM) and regression techniques
- Experience with Google Cloud Platform (BigQuery, Vertex AI)
- Background in CPG, retail, beauty, or e-commerce industries
- Experience with forecasting, promotional modeling, pricing analytics, marketing mix modeling, NLP/text analytics, or consumer behavior modeling
- Knowledge of NLP libraries (spaCy, NLTK, Hugging Face) or text mining techniques
- Familiarity with deep learning frameworks (TensorFlow, PyTorch) and interest in applying neural networks
Additional Benefits Information As Follows:
Salary Range: $98,400 - $140,200 (The actual compensation will depend on a variety of job-related factors which may include geographic location, work experience, education, and skill level)
- Competitive Benefit Package (Medical, Dental, Vision, 401K, Pension Plan)
- Hybrid Work Policy (3 Days in Office, 2 Days Work from Home)
- Flexible Time Off (Paid Company Holidays, Paid Vacation, Vacation Buy Program, Volunteer Time, Summer Fridays & More!)
- Access to Company Perks (VIP Access to L’Oréal’s Internal Shop for Discounted Products, Monthly Mobile Allowance)
- Learning & Development Opportunities (Unlimited Access to E-learnings, Lunch & Learn Sessions, Mentorship Programs, & More!)
- Employee Resource Groups (Think Tanks and Innovation Squads)
- Access to Mental Health & Wellness Programs
Don’t meet every single requirement? At L'Oréal, we are dedicated to building a diverse, inclusive, and innovative workplace. If you’re excited about this role but your past experience doesn’t align perfectly with the qualifications listed in the job description, we encourage you to apply anyways! You may just be the right candidate for this or other roles!
We are an Equal Opportunity Employer and take pride in a diverse environment. We would love to find out more about you as a candidate and do not discriminate in recruitment, hiring, training, promotion, or other employment practices for reasons of race, color, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or disability, or any other legally protected status.
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