Natasha
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Natasha

Economist · Data Scientist · ESG Analyst · Based in Germany

natashakabuka@gmail.com  |  LinkedIn  |  GitHub

View Projects →   About Me


What I work on

ESG Analytics

Climate scenario modelling, ESG Research and Analysis, supply chain risk, and sustainability data pipelines.

Econometric Research

Causal inference with instrumental variables, cross-country growth analysis, institutional economics.

Data Science

Supervised and unsupervised ML, predictive modelling, NLP, and statistical hypothesis testing.


Featured Projects

Institutions & Growth: IV Regression

3-endogenous-variable 2SLS replication of AJR (2001) and GLLS (2004). Human capital significant at p<0.01 across all specs.

Causal Inference 2SLS · Python · Stata

Nestle ESG Analysis

An Independent ESG Verification of Nestlé’s 2025 Commitments.

ESG Analysis · Python

Equity Analysis in Coffee Sustainability

This paper applies a lifecycle assessment (LCA) framework to evaluate coffee production and consumption through three sustainability pillars: environmental, economic, and social.

ESG Analysis · Python

Predictive Modelling for Agriculture

ML pipeline predicting agricultural outcomes from environmental and soil features.

Data Science Random Forest · XGBoost · Python

Hypothesis Testing: Men vs Women’s Football

Frequentist inference on scoring differences in international football matches.

Statistics t-test · Python

See all projects →


Skills

Languages

Python R Stata SQL

Libraries

pandas statsmodels linearmodels scikit-learn matplotlib seaborn

Methods

Instrumental Variables 2SLS Machine Learning Clustering NLP Monte Carlo Simulation Hypothesis Testing

Source Code
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# Natasha

::: {.tagline}
Economist · Data Scientist · ESG Analyst · Based in Germany
:::

[natashakabuka@gmail.com](mailto:natashakabuka@gmail.com) &nbsp;|&nbsp;
[LinkedIn](https://linkedin.com/in/natasha-kabuka/) &nbsp;|&nbsp;
[GitHub](https://github.com/tkay305)

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[About Me](about.qmd){.btn .btn-outline-secondary}

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---

## What I work on

::: {.grid}
::: {.g-col-12 .g-col-md-4}
::: {.domain-card}
### ESG Analytics
Climate scenario modelling, ESG Research and Analysis,
supply chain risk, and sustainability data pipelines.
:::
:::
::: {.g-col-12 .g-col-md-4}
::: {.domain-card}
### Econometric Research
Causal inference with instrumental variables,
cross-country growth analysis, institutional economics.
:::
:::
::: {.g-col-12 .g-col-md-4}
::: {.domain-card}
### Data Science
Supervised and unsupervised ML, predictive modelling,
NLP, and statistical hypothesis testing.
:::
:::
:::

---

## Featured Projects

::: {.grid}
::: {.g-col-12 .g-col-md-6}
[**Institutions & Growth: IV Regression**](projects/iv-institutions.qmd){.project-card}

3-endogenous-variable 2SLS replication of AJR (2001) and GLLS (2004).
Human capital significant at p<0.01 across all specs.

<span class="tag tag-research">Causal Inference</span>
<span class="tag tag-method">2SLS · Python · Stata</span>
:::
::: {.g-col-12 .g-col-md-6}
[**Nestle ESG Analysis**](projects/nestle_esg_analysis.qmd){.project-card}

An Independent ESG Verification of Nestlé's 2025 Commitments.

<span class="tag tag-esg">ESG</span>
<span class="tag tag-method">Analysis · Python</span>
:::
::: {.g-col-12 .g-col-md-6}
[**Equity Analysis in Coffee Sustainability**](projects/coffee_sustainability.qmd){.project-card}

This paper applies a lifecycle assessment (LCA) framework to evaluate coffee production and consumption through three sustainability pillars: environmental, economic, and social.

<span class="tag tag-esg">ESG</span>
<span class="tag tag-method">Analysis · Python</span>
:::
::: {.g-col-12 .g-col-md-6}
[**Predictive Modelling for Agriculture**](projects/agriculture.qmd){.project-card}

ML pipeline predicting agricultural outcomes from
environmental and soil features.

<span class="tag tag-ds">Data Science</span>
<span class="tag tag-method">Random Forest · XGBoost · Python</span>
:::
::: {.g-col-12 .g-col-md-6}
[**Hypothesis Testing: Men vs Women's Football**](projects/hypothesis-soccer.qmd){.project-card}

Frequentist inference on scoring differences
in international football matches.

<span class="tag tag-research">Statistics</span>
<span class="tag tag-method">t-test · Python</span>
:::
:::

[See all projects →](projects/index.qmd)

---

## Skills

**Languages**

::: {.skills-grid}
[Python]{.skill-badge} [R]{.skill-badge} [Stata]{.skill-badge} [SQL]{.skill-badge}
:::

**Libraries**

::: {.skills-grid}
[pandas]{.skill-badge} [statsmodels]{.skill-badge} [linearmodels]{.skill-badge}
[scikit-learn]{.skill-badge} [matplotlib]{.skill-badge} [seaborn]{.skill-badge}
:::

**Methods**

::: {.skills-grid}
[Instrumental Variables]{.skill-badge} [2SLS]{.skill-badge}
[Machine Learning]{.skill-badge} [Clustering]{.skill-badge}
[NLP]{.skill-badge} [Monte Carlo Simulation]{.skill-badge}
[Hypothesis Testing]{.skill-badge}
:::

© 2025 Natasha Kabuka

 

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