Ivan Palmegiani

Environemntal Data Analyst and Consultant

About Me

My expertise results from the fusion of ecosystem thinking and technical skills.

I hold expert knowledge and professional experience in biodiversity and wildlife monitoring, landscape ecology, as well as water and soil management. I'm familiar with European Union directives, and well informed about international initiatives and partnerships aiming at the conservation, restoration, and sustainable management of natural resources.

I can identify, collect and analyse quantitative data as well as satellite imagery to address pressing environmental issues involving land ecosystems, and make sense of the numerical results to identify risks and opportunities inherent each case study.

General Information

Berlin, Germany
English, Italian, Spanish, Portuguese, German

Technical and Organizational Skills

Python for Geospatial Analysis
R Spatial, Stats and Charts
Database Management in PostgreSQL-PostGIS
Remote Sensing in Google Earth Engine
Linux Bash & CLI Tools
Containerization in Docker
Just Enough
Physical & Mental Organization
Problem Solving
Very good
Very Good
Very Good
Very good

Work Experience

Geospatial Data Consultant at WWF Sweden
Contract, Home-based, Jul. 2021 - ongoing
Analysed data to estimate corporate water risks at site level | Generated data visualizations such as charts and maps | Produced reports and slide-shows presentations in accordance with WWF Water Risk Filter reporting process and standards

Tech stack: R Spatial, Tidyverse, R-Plotly, OfficeR, RStudio, MS Office, Conda, Git & GitHub.
Fellowship, Home-based, Apr. 2021 - ongoing
Proposal development with focus on GIS and Earth Observation technologies for the design of Nature-Based Solutions.
Geospatial Data Consultant at WWF Water Risk Filter
Contract, Home-based, Feb. 2021 - ongoing
Reviewed methodologies for corporate water risks assessment and scenarios analysis in close cooperation with the technical project manager | Designed data visualizations and maps of global water risks for efficient data communication in stakeholder engagement | Established automation workflows for data analysis and for data reporting

Tech stack: R Spatial, Tidyverse, R-Plotly, OfficeR, RStudio, MS Office, Conda, Git & GitHub.
Geospatial Data Scientist at SmartCloudFarming GmbH
Contract, Home-based, Mar. 2020 - Jan. 2021
Coordinated a small team of data professionals in a production context, i.e. research and development. Developed a minimum viable product (MVP) for soil moisture monitoring from Earth Observation data
  • Performed literature research to identify state-of-the-art methods for the estimation of soil water content and soil organic carbon from satellite imagery
  • Presented key findings in bibliographical reports
  • Identified suitable data sources to facilitate programmatic access to satellite imagery, and to ground data
  • Developed data science pipelines to source and composite satellite imagery to train machine learning models, and prepared ground data to test and validate predictions
  • Co-developed and fine-tuned ML models to predict soil moisture content from satellite data. The accuracy of predictions is satisfactory (R squared > 0.95, RMSE < 0.05)
  • Generated interactive data visualizations and 3D maps to report model predictions to executives
  • Developed dashboards to display ground data and model predictions to investors, and to potential clients
Tech stack: Python Spatial Modules, Jupyter, QGIS, Google Earth Engine, Scikit Learn, Python-Plotly, Streamlit, Conda, Git & GitHub, Docker, PostgreSQL-PostGIS, Google Cloud Platform, Google App Engine
Data Scientist at Earth Ratings UG
Contract, Home-based, May 2020 - Jun. 2020
Explored CDP data and methodologies | Identified additional data sources on Corporate Environmental Footprint (CEF) and Social Responsibility (CSR) | Developed a web scraper program to source publicly available data sets in accordance with the respective terms of use | Transformed unstructured data into to tabular formats and integration of open data sets from several sources | Exploratory analyses and visualization of the resulting data sets

Tech stack: all technical work was performed in Python
Data Management Consultant at University of Primorska
Contract, Home-based, Jan 2020
Revised data storage procedures at the Conservation and Population Genetic research group | Data wrangling | Migration from data sheets to relational database (ETL) | Automation of data queries | Advising the research team on data management

Tech stack: data wrangling in Python, user interfaces for data entry were generated with Microsoft Access
Professional Requalification at On-site and Online Training Institutes
Oct. 2018 - Nov. 2019
Data Science and Python programming courses | German language course | Conflict management and non-violent-communication (NVC) self-training | Personal development
Full-time, Berlin and Central Namibia, Apr. 2013 - Jun. 2018
Desk research activities:
  • Development of data collection protocols
  • Field project management
  • Planning and supervising field campaigns for the live-capture of cheetahs
  • Spatial and movement analyses of high-resolution GPS-telemetry data
  • Modeling distribution of the species and the use of space
  • Modeling individual movement patterns and interactions
  • Data management in Movebank
  • Design and maintenance of PostgreSQL-PostGIS database
  • Formulation and statistical testing of evolutionary hypothesis
  • Presenting scientific results to stakeholders and to the general public through talks, data visualizations and reports
  • Organization of scientific symposia
Field activities:
  • Undertaking live-capture campaigns of cheetahs using custom-build box traps
  • Assisting in the live-capture of leopards using custom-build box traps
  • Collecting and analyzing presence-absence data via camera-trap surveys
  • Engaging with local stakeholders and rural communities for the mitigation of human-wildlife conflict
  • Coordinating data collection in the field, supervising technicians and volunteers
Full-time, various areas of Portugal and Spain, Feb. 2012 - Feb. 2013
Field activities:
  • Undertaking live-capture campaigns of wolves
  • Collecting presence-absence data along transects and via camera-trap surveys
  • Engaging with rural communities in the attempt to mitigate human-wildlife conflict
Desk research activities:
  • Modeling species habitat, distribution and use of space with statistical learning models
Full-time, various areas of Italy, Nov. 2010 - Nov. 2011
Field activities:
  • Undertaking live-capture campaigns of wolves
  • Estimating pack size and reproductive success via wolf-howling surveys
  • Collecting presence-absence data along transects and via camera-trap surveys
  • Engaging with rural communities in the attempt to mitigate human-wildlife conflict
Desk research activities:
  • Biocustical analysis of wolves vocalizations
  • Ensuring proper storage and management of GIS data


Masters in Environmental Sciences and Natural Resources Management from University of Sassari
Grade: 110/110 Summa cum Laude, Jul. 2010
Systems ecology, landscape ecology, regional geology, pedology, sedimentology, wildlife conservation and management, conservation genetics, environmental modeling, statistical inference, advanced statistical theory, environmental economics

Training Courses

Danube Floodplain Management Technical University of Munich within EU Interreg Project
Sept. 2021
Principles of floodplain management and its relevance to EU legislation | Knowledge on technical aspects such as modelling, ecosystem services valuation, stakeholder engagement | Principles of feasibility studies and cost-benefit analysis | Presentation of newly developed Web-GIS tools for evaluating floodplains and their restoration potential
Advanced QGIS with Official Certification from Spatial Thoughts
Sept. 2021
Modeling and Automating GIS Workflows | Visualizing Time Series and 3D Data | Advanced Expressions
ARSET - Species Distribution Modeling with Remote Sensing from Applied Remote Sensing Training Program, NASA
Aug. 2021
Overview of Species Distribution Models (SDMs) | Data Sources for Species Distribution and Remote Sensing Data for Landscape Characterization | Tools for conducting SDM for a variety of ecosystems such Wallace R-based platform for modeling of species niches and distributions
ARSET - Satellite Observations and Tools for Fire Risk, Detection, and Analysis from Applied Remote Sensing Training Program, NASA
May 2021
Overview of Species Distribution Models (SDMs) | Data Sources for Species Distribution and Remote Sensing Data for Landscape Characterization | Terminology regarding type and components of fire (pre, during, post) | Climatic and biophysical conditions pre-, during-, and post-fire | The satellites and instruments used in conducting fire science | The applications of passive and active remote sensing for fires | How to visualize fire emissions and particulate matter | The use of tools for active fires, emissions, and burned areas | How to acquire data for conducting analysis in a given study area
Echoes in Space from EO College, European Space Agency & Friedrich-Schiller University Jena
Jul. 2020
History of Radar technology and the discovery of electromagnetic waves | Image acquisition | Geometry of airborne and space borne Radar systems | Land applications of Radar remote sensing | Applications of radar remote sensing over Water | Application of Radar remote sensing for Hazard management
Data Science Bootcamp from Business Trends Academy
Aug. 2019 - Nov. 2019
Data protection and ethical matters | Linear and nonlinear regression | A/B testing | Hypothesis testing | Data visualization in Tableau | Object oriented programming (OOP) | Python modules and functions | Pandas and NumPy | Multiprocessing and multithreading | RESTful API | Webscraping | Neural Networks and Machine Learning techniques | Keras and TensorFlow