ITACADEMYprojectes/ProjecteData
May 2025 – Jun 2025
2 Months active
Languages Used
CSVJSONJupyter NotebookMarkdownPython
Technical Skills
CSV ExportClusteringData AnalysisData CleaningData EngineeringData Extraction
María
PROFILE
María
Maria Uriburu developed a robust data engineering and analytics pipeline for the ITACADEMYprojectes/ProjecteData repository, focusing on financial analytics and risk assessment. She designed end-to-end data ingestion, cleaning, and preparation workflows using Python, Pandas, and Jupyter Notebooks, ensuring reliable and reproducible analysis. Her work included implementing exploratory data analysis, statistical validation, and predictive modeling with logistic regression to support finance-related decision-making. Maria consolidated datasets, managed repository documentation, and delivered interactive dashboards and KPI visualizations. The depth of her contributions is reflected in the integration of statistical testing, risk segmentation, and clear reporting artifacts, enabling informed business insights.
Overall Statistics
Feature vs Bugs
85%Features
Repository Contributions
81Total
Bugs
4
Commits
81
Features
23
Lines of code
297,963
Activity Months2
Your Network
36 people
Work History
June 2025
19 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for ITACADEMYprojectes/ProjecteData. Focused on delivering business-value features, stabilizing KPI presentation, and consolidating data pipelines for reporting. Highlights include risk analysis visualizations, KPI-related changes with a revert for stability, and consolidation of EFF 2022 data for notebooks and final reporting artifacts.
19 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for ITACADEMYprojectes/ProjecteData. Focused on delivering business-value features, stabilizing KPI presentation, and consolidating data pipelines for reporting. Highlights include risk analysis visualizations, KPI-related changes with a revert for stability, and consolidation of EFF 2022 data for notebooks and final reporting artifacts.
June 2025
May 2025
62 Commits • 21 Features
May 1, 2025May 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered a cohesive data engineering and analytics footprint enabling reliable data-driven decision making in finance analytics. End-to-end data ingestion and cleaning pipeline established, with final df_cleaned and robust duplicate handling. Completed Exploratory Data Analysis (EDA) with a comprehensive reporting script and final results that support governance and QA. Finance analytics delivered through KPI definitions, calculated metrics, and interactive dashboards, complemented by statistical validation (ANOVA, t-tests, and Mann-Whitney U) across key segments. Implemented predictive modeling and risk analysis with logistic regression for balance-default and related scenarios, including threshold balancing and currency considerations. Enhanced documentation and repository hygiene through updated READMEs, organized finance assets, sprint cleanup, URL fixes, and file recovery actions, strengthening reproducibility and collaboration.
May 2025
62 Commits • 21 Features
May 1, 2025May 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered a cohesive data engineering and analytics footprint enabling reliable data-driven decision making in finance analytics. End-to-end data ingestion and cleaning pipeline established, with final df_cleaned and robust duplicate handling. Completed Exploratory Data Analysis (EDA) with a comprehensive reporting script and final results that support governance and QA. Finance analytics delivered through KPI definitions, calculated metrics, and interactive dashboards, complemented by statistical validation (ANOVA, t-tests, and Mann-Whitney U) across key segments. Implemented predictive modeling and risk analysis with logistic regression for balance-default and related scenarios, including threshold balancing and currency considerations. Enhanced documentation and repository hygiene through updated READMEs, organized finance assets, sprint cleanup, URL fixes, and file recovery actions, strengthening reproducibility and collaboration.
Activity
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Quality Metrics
Correctness86.8%
Maintainability86.8%
Architecture81.8%
Performance80.0%
AI Usage22.0%
Skills & Technologies
Programming Languages
CSVJSONJupyter NotebookMarkdownPython
Technical Skills
CSV ExportClusteringData AnalysisData CleaningData EngineeringData ExtractionData ImputationData LoadingData ManagementData PreparationData PreprocessingData VisualizationData WranglingDecision TreesDocumentation
Repositories Contributed To
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