I am a Data Scientist, Machine Learning Engineer, and Data Engineer with over two years of professional experience building data-driven solutions, machine learning pipelines, and production-oriented analytics workflows.
I work primarily with Python, SQL, Scikit-learn, and cloud platforms to develop classification, regression, feature engineering, data preprocessing, model evaluation, and deployment solutions.
I have experience designing scalable ETL and data pipelines with Python, Spark, and PySpark, processing large structured datasets, and automating validation and reporting workflows.
I have contributed to geospatial and financial risk analysis systems, predictive reporting, fraud detection, recommendation engines, and operational analytics projects. My work includes integrating APIs, satellite imagery, dashboards, REST services, and machine learning models.
I am comfortable collaborating remotely with cross-functional teams and translating business, compliance, and operational requirements into practical analytical and machine learning solutions.
I am a native Spanish speaker with professional working proficiency in English, and I am focused on remote opportunities in data science, machine learning engineering, and data engineering.
Evaluated and validated large language model outputs for quality, consistency, and factual accuracy.
Detected inconsistencies, bias, and factual errors in AI-generated content while contributing to data quality improvements for model training and evaluation workflows. Worked under strict human review and quality assurance standards.
Designed and optimized automated data pipelines for geospatial and financial risk analysis using Python and Google Cloud Platform. Integrated satellite imagery and third-party mapping APIs into credit evaluation systems supporting machine learning risk scoring.
Performed preprocessing, validation, feature preparation, and quality control for machine learning workflows. Supported end-to-end ML deployment on GCP, contributing to an approximately 20% improvement in credit decision accuracy.
Automated data validation and preprocessing to reduce manual intervention and improve consistency. Collaborated remotely with cross-functional teams to deliver scalable solutions aligned with business and compliance requirements.
Designed and implemented ETL and reporting automation pipelines using Python and SQL, eliminating repetitive manual workflows.
Developed interactive Power BI dashboards and predictive reports for management decision-making. Reduced manual reporting time by approximately 30% through end-to-end process automation and scheduled refresh workflows.
Analyzed large structured datasets to identify business trends, KPIs, and actionable insights for commercial and financial teams. Maintained documented data workflows to ensure quality, consistency, and traceability.
Performed financial analysis and automated reconciliation processes to improve reporting accuracy and reduce processing errors.
Supported data-driven financial decisions through accounting systems and structured reporting tools. Improved cash-flow monitoring and regulatory compliance through systematic data review.
Data Science Bootcamp, Data Science
Completed a remote Data Science Bootcamp in Buenos Aires, Argentina, with more than 800 hours of training in data science, machine learning, analytics, and related projects.
Bachelor's Degree, Public Accounting
Bachelor's degree in Public Accounting completed in Ibagué, Colombia.
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