Founding Data Scientist

• Develop and refine quantitative models that estimate risk, value, and ROI using diverse real-world data sources.
• Analyze large, messy datasets to uncover patterns related to asset performance, loss drivers, and transition exposure.
• Partner with engineering to translate analytical frameworks into scalable, production-grade systems.
• Build scenario tools and sensitivity analyses to help clients understand financial outcomes under uncertainty.

The role helps cities and institutions reduce up to ~35% of emissions per asset and prevent ~40% of forecast climate-driven loss while improving ROI, addressing hidden financial risks in real estate and investment management.

• Bachelor’s or advanced degree in statistics, computer science, engineering, applied math, economics, or a related quantitative field.
• Strong analytical and statistical thinking, with experience working from first principles.
• Demonstrated ability to work with data using Python (pandas, numpy, scikit-learn) and SQL.
• Familiarity with cloud environments (AWS, GCP, or similar).
• Comfort working with location-based or geospatial data is a plus.
• Intellectual curiosity, comfort with uncertainty, and the ability to reason about financial implications from technical signals.
• Clear communicator with the ability to translate quant insights into understandable recommendations.

No specific benefits, compensation, or salary information provided in the job posting.

Mendria is a venture-backed, climate–fintech company that helps the world’s largest real estate owners and investment managers uncover and prevent hidden financial risks that traditional underwriting models miss, with a focus on sustainability and climate impact.