What I Bring to the Table
More than just tools — it's how I use them to make algorithms fairer
Look, I could list every library I've ever imported or every certification I've collected. But that's not what matters. What matters is that I know how to take messy data, build fair models, and ship code that doesn't screw people over.
My technical stack is built around one goal: creating AI systems that work for everyone, not just the people who look like the folks who built them. Here's what that looks like in practice.
Core Technical Skills
Programming & Machine Learning
Daily driver for everything from data pipelines to ML models. Pandas, NumPy, Scikit-learn — I dream in Python.
NLTK, spaCy, Hugging Face Transformers. Built custom text classification pipelines and fine-tuned language models.
TensorFlow, PyTorch, Scikit-learn, LightGBM. Comfortable building everything from logistic regression to deep learning.
Queries, joins, database design. Built normalized SQLite databases for production applications.
AI Fairness & Ethics
Built bias detection frameworks from scratch. Implemented demographic parity, equal opportunity, disparate impact ratio.
Pre-processing, in-processing, and post-processing techniques. Reweighting, threshold optimization, fairness constraints.
Not just gender or race — analyzing bias across multiple marginalized identities simultaneously. This is my superpower.
Data Science & Visualization
Pandas, NumPy, data cleaning, feature engineering. Processed 140k+ records with complex ETL pipelines.
Matplotlib, Seaborn, Plotly. Built interactive dashboards and publication-ready charts that actually tell a story.
When you need to talk to non-technical stakeholders, these are the tools. Dashboards, pivot tables, business analytics.
Cybersecurity & Data Governance
Implemented DLP solutions at EY and HSBC. Data classification, policy enforcement, incident response.
Privacy by design, data protection impact assessments, regulatory compliance frameworks.
Enterprise data governance platforms. Certified in OneTrust and Collibra.
Development Tools & Workflows
Version control, branching strategies, pull requests, code reviews. All my work is version-controlled.
Built 800+ line interactive apps. Comfortable deploying ML models as web applications.
My daily workflow. Notebooks for exploration, IDE for production code.
Languages I Speak
Code isn't the only language I'm fluent in
Portuguese
Native
Mother tongue — the language of home and heart
English
Fluent
Academic and professional proficiency
Polish
Intermediate
Lived in Kraków, still working on perfecting those consonant clusters
French
Intermediate
Can read Foucault in the original (slowly)
Spanish
Intermediate
Close enough to Portuguese that I can fake it
Some Certifications (If You Care About That)
Plus 30+ other certificates from various training programs. They're nice to have, but honestly? The real proof is in the work.
Want to See These Skills in Action?
Check out my projects to see how I use this tech stack to build fairer AI systems. Or let's talk about how we can work together.