Resume

Economics graduate (PUCP, 2018–2025) specialized in statistics, econometrics, and applied data science. Expert in ETL pipelines, large-scale data extraction, and automation with Python and SQL; experienced with interactive dashboards in Power BI and Bokeh. Applied Machine Learning (including Computer Vision) and integrated Generative AI for automated reporting and advanced analysis. Recognized for analytical thinking, data accuracy, and turning complex information into high-impact solutions.

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Summary

Karl Willem Janampa Aparicio

Economics graduate from the Pontifical Catholic University of Peru (PUCP), specializing in statistics, econometrics, and applied data science. Expert in ETL processes, large-scale data extraction, and pipeline automation with Python and SQL, with proficiency in visualization tools such as Power BI. I have applied Machine Learning to predictive modeling and Computer Vision, and integrated Generative AI through prompt engineering to automate reporting and advanced analysis. Recognized for analytical thinking, accuracy in data handling, and the ability to turn complex information into high-impact solutions. I am seeking new challenges to apply my data science expertise across different domains and generate strategic value.

Education

Bachelor’s Degree in Economics

2018 – 2025

Pontificia Universidad Católica del Perú (PUCP)

Languages

  • English — B2 (Intermediate), 2019–2025 — PUCP, Faculty of Economic Sciences

Training & Certifications

  • Data Visualization & Analytics with Power BI — 2024 — Faculty of Economic Sciences
  • Complementary Software Training — 2019–2021 — CEDHINFO, Lima, Peru
    • SQL Server — relational database design and management
    • Advanced Excel — analytics, visualization, and macros
    • Power BI — interactive dashboards

Recognitions

  • 2025: “Junior Researchers” — APE 2025 Congress, selected to present bachelor’s thesis.
  • 2025: Second Winter School — Advanced Methods for Social Sciences, organized by PUCP’s Q-LAB.

Skills & Tools

Technical Competencies

  • Statistical Analysis & Econometrics
  • Machine Learning & Data Science
  • Natural Language Processing (NLP)
  • ETL & Big-Data Processing
  • Dashboards & Data Visualization (Power BI, Bokeh)
  • Databases: SQL Server
  • Advanced Excel (macros)
  • Python (pandas, scikit-learn, Matplotlib, etc.)

Software Proficiency

  • Advanced: Python, SQL, Excel, Power BI
  • Intermediate: Stata, R
  • Basic: MATLAB

Professional Experience

Research Assistant in Artificial Intelligence & Data Science — Prof. Alexander Quispe

2024 – Present

Lima, Peru

  • Led spatial analysis with raster data to measure representativeness of economic activity and evaluate social, economic, and technological impacts.
  • Automated and optimized data pipelines with Python and SQL (ETL, cleaning, transformation), including performance and cost indicators.
  • Processed and analyzed international datasets, including Bangladesh (economic activity) and Ookla (internet outages and connectivity phenomena).
  • Developed web scraping and big-data extraction from GitHub and LinkedIn APIs for labor-market studies and developer-activity analytics (e.g., Bangladesh developer ecosystem).
  • Optimized and debugged Python code for the Synthetic Difference-in-Differences (SynthDiD) method, improving efficiency versus widely used implementations in the d2cml-ai organization (e.g., synthdid.py, csdid notebooks).
  • Built data-driven applications, including:
    • Nearest Company Locator — geospatial tool to locate nearby firms using cleaned, standardized datasets.
    • Pothole Detector — road-infrastructure detection with YOLOv and Computer Vision techniques.
    • Lightweight geolocation apps for spatial identification of constructions, events, and zones using location data.
  • Implemented NLP models for NAICS classification via Azure AI Language Studio and models such as BERT, RoBERTa, T5, and LLaMA.
  • Created interactive dashboards with Power BI and Bokeh for dynamic reporting and stakeholder-ready insights.
  • Cost & efficiency analysis of AI/ML tooling and data services, assessing economic impact of:
    • Azure AI services for NLP and Computer Vision,
    • GitHub APIs for large-scale data extraction, and
    • Claude APIs for automated text generation and processing.

Reference

Prof. Alexander Quispe, The World Bank – Microsoft
Email: alexander.quispe@pucp.edu.pe · Phone: +1 (571) 440-3124

Projects

Data Science Project — Predictive Modeling to Optimize Solar Panel Angle

2025

Ayacucho, Peru

  • ETL, balancing and preprocessing to ensure data quality and consistency.
  • Implemented Python models (Random Forest, Gradient Boosting, Clustering).
  • Cross-validation and hyperparameter tuning to improve accuracy and robustness.

Bachelor’s Thesis (in progress) — Impact of ChatGPT on Software Development for Data Science

2024 – 2025

Lima, Peru

  • ETL in Python to extract and clean data from GitHub repositories.
  • Applied econometric methods: Difference-in-Differences, Synthetic Control, and Staggered DiD.
  • Automated interactive reports with dynamic visualizations to communicate key findings.