About me

I'm a Data Scientist with a PhD in Physics specialising in decarbonisation and sustainability. Passionate about problem-solving, I apply my strong mathematical and statistical skills to tackle complex challenges in sustainability.

After relocating from Australia back to Europe, I’m seeking opportunities to work on meaningful problems that require analytical thinking and technical expertise. With a PhD in Physics, I bring a deep understanding of modeling, data analysis, and computational techniques.

In my current role, I help companies measure and reduce their carbon footprint (Scope 1, 2, and 3), assisting with data collection and crafting SBTi-aligned mitigation strategies. For Australian fashion brands, I developed a textile emissions database using SimaPro to provide accurate impact assessments. I also led the data analysis for a major food waste reduction project in New Zealand, identifying key waste drivers across 100+ restaurants and proposing five actionable reduction strategies.

Beyond my professional work, I enjoy developing simulations and applications that model natural processes. My blog explores topics like diffusion, moisture transport, and climate dynamics—bringing scientific concepts to life through code.

Resume

Experience

  1. Decarbonisation Associate

    Edge Impact

    2025 — present

    Support on selected decarbonisation and emission mitigation projects as a freelancer

  2. Decarbonisation Analyst

    Edge Impact

    2024 — 2025

    Conducted carbon footprint assessments for 10+ companies, supporting data collection and developing SBTi-aligned decarbonisation pathways.
    Created textile emission database for Australian fashion companies using SimaPro assessing textile production impacts from production of raw materials until sale in shops.
    Led data analysis for a food waste reduction project in New Zealand, identifying key waste drivers and developing five actionable reduction strategies for restaurants.

  3. PhD Researcher

    UNSW Sydney

    2019 — 2023

    Implemented machine learning algorithms into state-of-the-art data analysis leading to a speed-up of the calculation by a factor of 100.
    Created Bayesian Optimisation algorithm for high-performance computing on Linux supercomputers to work with large data sets.
    Lead cross-functional collaborations across 5 different research institutes resulting in 3 first-author publications in top-tier journals.

Education

  1. PhD - Physics University of New South Wales Sydney

    2019 — 2023

    PhD in Theoretical Physics focussing on Machine Learning and optimisation applied to cosmological data using high-performance computing servers.

  2. Master - Physics Universität Heidelerbg

    2016 — 2019
  3. Bachelor - Physics TU Darmstadt

    2012 — 2015

Blog

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