Data Scientist - Environmental Intelligence (Fashion)

Carbonfact; Paris; Hybride; EUR 55 000 - 74 000; Plein temps

Avantages offerts par ce poste

Health insurance

Annual learning budget

Team retreats

Equity package

Office in Paris with flexible remote

Compensation framework with salary & 0

Résumé du poste

Carbonfact is hiring a Data Scientist to join its Environmental Intelligence Platform for the fashion industry. You will transform messy BOMs, catalogs, and purchase data into reliable data models, detect anomalies, and enrich data for accurate footprint measurements.

You will work closely with client data, join calls, and occasionally visit brands onsite, translating data quality into real environmental impact improvements.

Qualifications

• 2+ years of professional experience in data-oriented roles.
• Strong Python skills and ability to write production-grade code.
• Experience with NLP basics: regex, typo handling, normalization.
• Familiarity with analytics engineering and data modeling concepts.
• Excellent verbal and written English for customer discussions.
• Exposure to real-world, heterogeneous datasets and data quality judgment.

Responsabilités

• Parse, normalize, and transform raw client data into Carbonfact's internal models.
• Build and improve automated gap-filling and anomaly detection on customer datasets.
• Develop analytics on customer data for internal use and external presentation to brands.
• Contribute to building and improving the Carbonfact platform.
• Collaborate with Customer Operations and Science teams to deliver value.
• Lead conversations with customers and influence data integration discussions.

Connaissances

Python

SQL

NLP basics

Analytics engineering

English communication

Agentic engineering

Outils

GitHub Copilot

Description du poste

Carbonfact is hiring a Data Scientist to join its Environmental Intelligence Platform for the fashion industry. You will transform messy BOMs, catalogs, and purchase data into reliable data models, detect anomalies, and enrich data for accurate footprint measurements.

You will work closely with client data, join calls, and occasionally visit brands onsite, translating data quality into real environmental impact improvements.