Puig Data Analytics Demand Planning Graduate
- Employment
- Temporary
- Seniority
- Entry-Level
- Posted
- Mar 29, 2026
About Puig
Puig is a privately held Spanish fragrance and fashion company that manages a portfolio of owned and licensed premium brands. Renowned for combining creativity with commercial acumen, Puig operates across product design, marketing and global distribution and offers an international, brand-driven environment within a family-led group.
Puig in Barcelona seeks a Data Analytics Demand Planning Graduate (temporary) to support forecasting, data analysis and S&OP activities.
Role & Responsibilities
- Support the demand planning cycle by consolidating sales and inventory data to produce regular forecasts and cadence reports.
- Perform quantitative analysis and time-series forecasting to identify demand patterns, seasonality and outliers.
- Prepare and maintain dashboards and visualisations to communicate forecast accuracy, bias and inventory KPIs to cross-functional stakeholders.
- Collaborate with commercial, supply chain and production teams to translate promotional plans and market intelligence into demand assumptions.
- Contribute to continuous improvement initiatives around forecasting methodology, data quality and process automation.
- Execute ad-hoc analyses to investigate SKU-level performance, stock variances and replenishment needs.
- Assist with the reconciliation of forecast-to-sales and support monthly S&OP review materials.
- Document analytical procedures and ensure traceability of assumptions used in planning models.
Qualifications
- Bachelor’s or Master’s degree in Supply Chain Management, Industrial Engineering, Statistics, Mathematics, Economics, Data Science or a related quantitative discipline.
- Strong analytical mindset with demonstrable experience in statistical or forecasting techniques through internships, academic projects or entry-level roles.
- Excellent numerical literacy and attention to data quality and detail.
- Effective communicator, able to present analytical findings clearly to commercial and operational partners.
- Proactive, methodical and comfortable working within cross-functional teams in a fast-paced environment.
- Fluent in English; additional languages are advantageous.
Skills
Experience
Entry-level position targeted at recent graduates or candidates with internship/work placement experience in demand planning, supply chain analytics or commercial analytics. Prior exposure to forecasting projects, inventory analysis or S&OP support is preferred.
Education
Bachelor’s or Master’s degree in Supply Chain, Industrial Engineering, Statistics, Mathematics, Economics, Data Science or a related quantitative field.
Workplace
The role is situated in Barcelona, Catalonia, Spain.
Culture
Puig cultivates a creative, entrepreneurial culture that balances heritage craftsmanship with commercial rigour. The organisation values cross-disciplinary collaboration, international mobility and professional development within a brand-centric environment.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Puig, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Junior Demand Planner — Data Analytics», «Graduate Demand Forecasting Analyst», «Supply Chain Data Analyst (Graduate)», «Demand Planning and Analytics Associate», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.