Worldly is looking for a Data Scientist to help transform complex sustainability data into actionable insights that can deliver environmental impact reductions at scale for the consumer goods industry, focusing on graph network analysis and AI-driven qualitative data modeling to reveal patterns across global supply chains and build predictive capabilities.
Requirements
- Proficiency in Python (pandas, scikit-learn, networkx, PyTorch, spaCy, or similar).
- Strong SQL skills and experience working with Postgres.
- Familiarity with AWS and Git-based version control
- Familiarity with graph databases and AI/NLP methods for text data.
- Experience with predictive modeling, causal inference, simulating “what-if” interventions or Bayesian analysis.
Responsibilities
- Build and analyze graph models of supply chains, product relationships, and sustainability impact networks.
- Apply NLP and AI methods to extract insights from qualitative data (e.g., sustainability reports, industry assessments).
- Develop predictive and forecasting models that help customers test and optimize strategy decisions.
- Design analytical workflows integrating with our Postgres data warehouse and Cube semantic layer.
- Partner with engineers and sustainability experts to translate analytics into real-world impact.
Other
- 4-10 years of experience in data science or analytics
- Excellent communication skills and a passion for sustainability.
- Experience working with sustainability, ESG, or supply chain data
- US - Remote
