The organization is looking to convert complex sustainability data into actionable insights for environmental impact reductions in the consumer goods industry, with an emphasis on graph network analysis and AI-driven qualitative data modeling.
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 working with sustainability, ESG, or supply chain data is helpful.
- Experience with predictive modeling, causal inference, simulating “what-if” interventions, or Bayesian analysis is beneficial.
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 such as sustainability reports and industry assessments.
- Develop predictive and forecasting models to help customers test and optimize strategy decisions.
- Design analytical workflows integrating with the Postgres data warehouse and Cube semantic layer.
- Collaborate 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.
- 90% employee premium and 75% spouse/dependent premium covered for healthcare.
- Company-sponsored 401k with up to 4% match.
- 100% Parental Paid Leave.
