L’Oréal is hiring for a Data Science Intern role in Mumbai, Maharashtra. This internship offers an exciting opportunity for students who want to combine data science, scientific research, analytics, and communication in one of the world’s largest beauty and innovation companies.
If you are pursuing a Master’s degree in Data Science, Bioinformatics, Computational Biology, Statistics, or Applied Mathematics, and have strong skills in Python, R, data analysis, and visualization, this internship could be an excellent career-building opportunity.
About the Company
L’Oréal is the world’s leading beauty company, operating in 150+ markets worldwide. For over 100 years, L’Oréal has been at the forefront of beauty innovation by combining:
- Science
- Technology
- Data
- Research
- Sustainability
The company invests heavily in Research & Innovation (R&I) to create high-performance products across skincare, haircare, cosmetics, and dermatological solutions.
L’Oréal’s R&I division includes over 4,100 experts working in:
- Skin science
- Hair science
- Microbiome research
- AI-driven product innovation
- Advanced formulation development
The company leverages modern technologies such as AI, data science, computational modeling, and analytics to accelerate innovation.
Internship Overview
This role is specifically for the Scientific Communications & Data Science team within L’Oréal’s Research & Innovation department in Mumbai.
As a Data Science Intern, your work will not be limited to coding or dashboards. You will contribute to:
- Scientific intelligence gathering
- Research analysis
- Literature mining
- Data structuring
- Insight generation
- Scientific communication
This makes the internship highly unique because it combines technical data skills with scientific thinking and business communication.
Salary / Stipend 💰
Official Stipend: Not disclosed by L’Oréal
Estimated Stipend
Based on similar internships at large MNCs in India, the expected stipend is:
₹30,000 – ₹60,000/month (Estimated)
Estimated Total Earnings
| Duration | Earnings |
|---|---|
| 1 Month | ₹30,000 – ₹60,000 |
| 3 Months | ₹90,000 – ₹1.8 Lakh |
| 6 Months | ₹1.8 – ₹3.6 Lakh |
This estimate is based on internships at companies such as:
- L’Oréal
- Unilever
- Procter & Gamble
Actual compensation may vary depending on internship duration and department.
Job Location
| Criteria | Details |
|---|---|
| Role | Data Science Intern |
| Company | L’Oréal |
| Location | Mumbai |
| Mode | Onsite |
| Department | Research & Innovation |
This is an onsite internship, so candidates should be prepared to work from Mumbai.
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Key Responsibilities
The role includes multiple responsibilities across research and analytics.
1. Scientific Intelligence
You will analyze and synthesize scientific literature across key innovation areas.
Tasks may include:
- Research paper mining
- Extracting useful insights
- Identifying research gaps
- Trend analysis
- Opportunity discovery
This helps L’Oréal identify future innovation directions.
2. Content Creation
A major part of the role involves converting technical scientific findings into understandable insights.
You may work on:
- Scientific summaries
- Research reports
- Insight decks
- Internal knowledge documents
- Digital presentations
This requires both technical and communication skills.
3. Data Analysis & Visualization
You will build analytical tools and dashboards to help teams understand complex datasets.
This may involve:
- Data cleaning
- Feature engineering
- Statistical analysis
- Dashboard creation
- Data storytelling
Visualization helps decision-makers quickly interpret data.
4. Event Strategy Support
You may assist in research-focused events and dermatology congresses.
Responsibilities include:
- Planning support
- Material preparation
- Post-event reporting
- Scientific communication
This gives exposure beyond pure technical work.
5. Project Coordination
You will coordinate with internal teams to ensure project execution runs smoothly.
This includes:
- Documentation
- Workflow management
- Cross-functional communication
- Deliverable tracking
Required Skills
L’Oréal seeks candidates with strong analytical and technical capabilities.
Python
Python is one of the most important skills for this internship.
Useful Python libraries include:
- Pandas
- NumPy
- Matplotlib
- Scikit-learn
- SciPy
Python helps with:
- Data processing
- Statistical modeling
- Automation
- Visualization
R
R is widely used in statistics and research-heavy environments.
R is useful for:
- Statistical analysis
- Experimental studies
- Hypothesis testing
- Scientific research
Power BI
Microsoft Power BI knowledge is highly valuable.
Power BI helps create:
- Interactive dashboards
- Reports
- Visual analytics
- Business intelligence insights
Data Mining & Structuring
Candidates should understand:
- Structured data
- Unstructured data
- Data cleaning
- Feature extraction
- Data transformation
These are core data science skills.
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Educational Requirements
Candidates should currently be pursuing a Master’s degree in fields such as:
- Data Science
- Bioinformatics
- Computational Biology
- Statistics
- Applied Mathematics
A Life Sciences background is a strong advantage because this role intersects with scientific research.
Relevant life science knowledge includes:
- Biology
- Dermatology basics
- Skin science
- Research methodology
How to Apply
To maximize your chances:
- Highlight Python/R projects
- Include dashboards built in Power BI
- Showcase research or thesis work
- Add publications or scientific presentations if available
- Emphasize communication skills
A strong resume for this role should show both:
- Technical depth
- Scientific curiosity
Apply by clicking the button below and ensure your application demonstrates your research mindset, analytical strength, and ability to communicate complex scientific insights clearly.
Disclaimer: This internship information is collected from official/public sources for informational purposes only. We do not charge any fees, do not guarantee recruitment or selection, and are not responsible for any loss or decisions made based on this information.
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