Varvara Vladimirova

As a quantitative ecologist and spatial data analyst, I focus on modelling how wildlife move, interact with landscapes, and respond to environmental change. My work is centred on data-driven analysis, including movement modelling, spatial statistics, GIS, and predictive modelling for conservation and climate-related questions. I have a strong technical background in R, GIS tools (QGIS, ArcGIS Pro), and statistical modelling, and I am expanding my expertise into Python and remote-sensing workflows. My research integrates large telemetry datasets, environmental rasters, and landscape features to generate actionable insights for management and planning. My experience includes collaborating with government agencies, research teams, and conservation partners, producing maps and models that support ecological decision-making. I combine analytical modelling with targeted field experience, allowing me to translate real-world ecological processes into robust spatial and computational approaches.

I am a spatial data researcher with experience in GIS, remote sensing, wildlife movement analysis, and statistical modelling (GLM/GLMM, RSFs/SSFs, cross-validation, spatial statistics). I have worked on projects involving habitat mapping, disturbance time-series analysis, and landscape connectivity. I’m comfortable working with R and ArcGIS Pro and am currently expanding into Python and remote sensing workflows. I’m seeking a position where I can apply and grow my skills in spatial analysis, ecological modelling, and environmental data workflows.

Specialised in ecological modelling, spatial data analysis, and forecasting caribou distributions under global change (landscape and disturbance changes). My work involves advanced statistical modelling (e.g., conditional process analysis), large-scale ecological datasets (25+ years of caribou data), computational tools in R, Python, and Julia, and HPC clusters. I lead interdisciplinary collaboration with statisticians, geneticists, ecologists, and governmental agencies.