I bring a unique blend of engineering training and a PhD in climate modeling (computational geoscience), combined with over six years of experience across both industry and research. My expertise lies in applying advanced computational skills—including Earth Observation Data Science, Geospatial Data Engineering, Machine Learning, Artificial Intelligence, Physics-based Numerical Modeling, High-Performance Computing, Cloud Computing Architecture (AWS, Oracle, Azure, GCP, OpenStack), and Time Series Modeling—to solve complex, real-world problems.
I have delivered impactful solutions in diverse fields such as weather forecasting, geophysics, water resource management, geotechnical engineering, software development, climate and weather risk modeling, and the reinsurance industry. Collaborating with multinational teams has made me highly adaptable, culturally agile, and an effective team player.
Currently, I apply my multidisciplinary expertise in geospatial analytics and weather and climate risk modeling within the reinsurance industry (Property & Casualty insurance). My focus spans natural catastrophes (e.g., tropical cyclones, flooding), agricultural risks, weather derivatives, and business interruption risks. Additionally, I am developing and maintaining geospatial data infrastructure on AWS to enable remote querying and generative AI analytics of satellite datasets, integrated with Azure DevOps pipelines to drive actionable business insights.
Experience: Parametric Reinsurance & Climate Risk Specialist | Geospatial Analytics Solutions Expert | Climate & Weather Data Scientist and Engineer | Environmental Scientist | Geotechnical & Geophysical Engineer | Python Software Developer | AWS Solutions Architect | Generative AI Enthusiast
I have contributed to developing and underwriting parametric and index-based reinsurance solutions and developing software platforms for satellite-based CO2 emissions and wildfire burned area monitoring. Proven expertise in Natural Catastrophe modelling (Tropical Cyclone, Earthquake, Flooding, SCS, Wildfire, etc.), climate risk assessment, and insurance structuring product development, leveraging deep knowledge of the (re)insurance value chain to design scalable, client-focused solutions. Adept at using machine learning, spatial data engineering, satellite and meteorological data processing, and time series analysis to price and innovate climate-linked insurance products.
Skilled in Python, R, SQL/NoSQL, and cloud platforms (AWS, Azure, GCP) with a passion for building robust tools that drive automation and analytics at scale. Successfully led the deployment of a cloud-based parametric pricing platform and worked cross-functionally with technical and commercial teams to deliver impactful solutions. An exceptional communicator and collaborator, capable of translating complex datasets into actionable insights for clients and stakeholders.
Research: My research explores how hazard, exposure, and vulnerability interact to shape risk and impact from extreme weather events, today and under a changing climate. I combine modelling with systems thinking across tropical cyclone, hail, and severe convective storm modelling, and quantify how these events translate into financial impacts for companies, cooperatives, and real estate. I'm also developing data-driven adaptation solutions that help companies quantify the financial benefit of specific adaptation measures against storm, flood, and wildfire risk.
Hobby: I love to volunteer for societal-building activities, enjoy playing and watching (Chelsea FC fan for life!) football, am passionate about new technology, and like spending time with my family. I am mostly coding and reading about APIs for new challenges.
7+
Research & Industry
Projects
60+
Citations
6+
Solutions Deployed
AWS & Azure
7+
Published Papers
in High Impact Journals
7+
Conference Abstracts
(e.g., EGU, AGU)
4+
Invited
Talks
2026.07 - present
Physical climate risk modelling and adaptation measures. Responsible for modelling tropical cyclone, extratropical cyclone, and severe convective storm risk to help banks, real estate, and corporates estimate their physical climate risk and build financial resilience.
2025.02 - 2026.06
Geospatial data analysis, Natural catastrophe modeling, Parametric insurance pricing, Machine learning, Climate risk assessment, and Cloud computing.
2024.5 - 2025.01
Teaching Climate Modelling and Climate Dynamics courses to Masters students in Applied and Environmental Geoscience (AEG), Physics, Mathematics and Computer Science departments.
2021.04 - 2024.04
Climate modeling, climate dynamics, machine learning, empirical statistical downscaling, climate and topography interactions and stable isotope modelling.
2023.07 - 2024.03
Platform engineer for analytic solution of atmospheric CO2 emissions for countries and regions using NASA satellite XCO2 measurements.
2019 - 2021
Developed temperature calibration software on Raspberry Pi environment: flight temperature sensor control, voltage and pressure control into the calibration chamber and data analysis.
2018 - 2021
Scientific python module development: pyESD (empirical statistical downscaling), pyClimat (visualization tools for climate model output) and running climate simulations on Linux High Performance Computing environment.
2019 - 2020
Running bioelectric reactor to isolate H2-producing bacteria: Analytical chemistry, molecular biology and biotechnology techniques.
2017 - 2020
Specialization in Hydrogeological and climate modeling. Master thesis: Prediction of precipitation response to 21st century climate change in the Ammer catchment (South-west Germany): Using Machine Learning algorithms.
Grade: First Class
2017 - present
Assisting lectures in Geotechnical engineering, Geophysics, Rock Mechanics, Hydrogeology, and computer programming.
2017 - present
Bachelor thesis: Mapping of subsurface fracture characteristics using geoelectrics.
Grade: First Class
Physical climate modelling, natural catastrophe risk, and parametric insurance — roughly every two weeks.
The previous post covered how tropical cyclone risk gets modelled. This one covers what happens once that risk needs to be transferred — and increasingly, the answer is parametric insurance rather than a traditional indemnity policy.
Read full post →Tropical cyclones are the costliest natural peril on the planet — a single landfalling storm can generate tens of billions of dollars in insured and uninsured losses within days. For decades, quantifying that risk was the job of a handful of catastrophe modelling firms serving (re)insurers. That has changed. Banks assessing mortgage and corporate loan...
Read full post →Curated news and research on physical climate risk, with a focus on tropical cyclone, severe convective storm and flood perils relevant to (re)insurance — pulled from journals, catastrophe risk vendors, and reinsurer publications.
Governor Signe Krogstrup on financing the green transition and climate adaptation Danmarks Nationalbank
Read source →Data centre investors underestimate climate risks, see these as ‘not a priority’: report The Business Times
Read source →Data Center Investors Underestimate Climate Risk, Report Says Bloomberg.com
Read source →I think I am very friendly and nice enough to work with everyone or team. I am a problem solver and passionate about open source software development. I mostly reply to emails within 3 hrs. Kindly link up for collaboration or information related to any of my projects.
: Tübingen, Germany
: dannboateng@gmail.com
: Department of Geoscience, University of Tübingen
: +491783012296
: German (Intermediate), English (Advanced), Twi (Advanced)