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Paula Cadena

@paulacadena

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Data Scientist skilled in machine learning and data analysis.

United States

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What I'm looking for

I am looking for a collaborative environment that values data-driven decision-making and offers opportunities for professional growth.

I am a dedicated Data Scientist with a strong foundation in computational analysis and public policy, holding a Master's degree from The University of Chicago. My academic journey has equipped me with a robust skill set in programming, machine learning, and data engineering, allowing me to tackle complex data challenges effectively.

Throughout my professional experience, I have successfully applied advanced statistical models and machine learning techniques to derive actionable insights from large datasets. At The University of Chicago, I contributed to peer-reviewed research by analyzing socioeconomic factors affecting early childhood development, while my internship at the Crime and Education Lab honed my skills in natural language processing and predictive modeling. I am passionate about using data to inform policy and drive positive change.

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Experience

Work history, roles, and key accomplishments

Current

Research Assistant

Current

The University of Chicago Center for the Economics of Human

May 2024 - Present (1 year 6 months)

Applied logistic regression models in Stata/R to analyze longitudinal datasets (10,000+ observations), identifying socioeconomic factors impacting early childhood development. Designed mediation analysis frameworks to isolate the effects of family endowments vs. environmental factors, informing policy recommendations adopted by 3 state agencies.

Logistic Regression Stata R Data Analysis Policy Recommendations Python Data Validation

Data Analytics Intern

The University of Chicago Crime and Education Lab

Jul 2024 - Present (1 year 4 months)

Developed a Python-based NLP pipeline (NLTK, SpaCy) to extract unstructured data from 500+ PDF reports, uncovering district-level disparities in pandemic learning loss. Engineered a gradient boosting model (XGBoost) to predict student performance gaps, enabling targeted tutoring for 1,200+ students with 92% precision.

Python NLP NLTK

Graduate Teaching Assistant

The University of Chicago Booth School of Business

Jan 2024 - Present (1 year 10 months)

Guided 25 students weekly in person with course requests, office hours, and learning opportunities with code reviews and data analytics; fostered a collaborative learning environment with a focus on R and Python. Evaluated individual and group assignments for over 100 students, graded exams and final projects, and collaborated with a team of 5 TAs to design challenging data analysis questions for

R Python Data Analytics

Data Integration Consultant

The Special Jurisdiction for Peace - Colombia

Aug 2023 - Present (2 years 3 months)

Led end-to-end ETL pipeline development (Python, Pandas) to migrate 1.48TB of legal data, standardizing metadata and reducing manual errors by 40%. Built a React.js search interface integrated with PowerApps, slashing file retrieval time by 60% for 30+ legal teams handling 50,000+ victim cases.

ETL Python Pandas

Senior Data Analyst

Bogota Chamber of Commerce

Feb 2022 - Present (3 years 9 months)

Deployed a machine learning classifier (Random Forest, Scikit-learn) to segment 2M+ companies, achieving 85% test accuracy and reducing manual segmentation effort by 50%. Designed real-time Power BI dashboards tracking 20+ KPIs, enabling 60+ stakeholders to monitor program performance and adjust strategies.

Machine Learning Random Forest scikit learn

Academic Manager of Postgraduate Programs

University of Los Andes Department of Economics

Feb 2020 - Present (5 years 9 months)

Automated document generation workflows (Power Automate, Python), reducing manual steps from 9 to 3 and cutting response time by 50%. Integrated SQL databases with student portals, enabling real-time tracking of academic progress for 350+ students.

Power Automate Python SQL R