I’m Olivera, a founder of spacebayes, an early-stage Data-as-a-Service startup for crop yield forecasting and physical climate risk. We give trading desks, insurers, reinsurers and food companies early forecasts at national and county levels, together with uncertainty estimates. For that, we’re building our own data infrastructure and fusing satellite (hyperspectral, optical and thermal), climate, weather and historical data.

I have six years of industry experience as a data scientist, where I focused on geospatial and Bayesian models, with applications in finance, supply chain and regional economic forecasting.

I got a PhD in Cognitive Science from Osnabrück University, where I worked on interpretable machine learning for real-world applications, like public health and environmental sciences. Previously, I studied Physics (BSc) at the University of Novi Sad, Serbia.

My work includes developing Bayesian models for:

• predicting leaf area index (LAI) from reflectance spectra of winter wheat,
• predicting the spread of infectious diseases in German counties and
• predicting concentrations of particulate matter (PM2.5) across counties in California.

My hobby is analog photography, hiking and educating (aka bothering) my friends and family with David Lynch filmography.