Excellent Communication Skills: Successfully interacted with four operations managers from Seguros Bolivar, Credivalores, Jelpit, and Bancolombia.
Automated Visual Dashboard in Power BI: Developed an aesthetically pleasing automated dashboard in Power BI, integrating data from Seguros Bolivar. This dashboard encompasses over a million monthly transactions,
leveraging SQL Server and advanced job and stored procedure management.
Complete Automation of Credivalores’ Weekly Emmaster Hours: Automated the entire process of calculating and extracting values from Credivalores’ weekly
Emmaster hours using SQL and Visual Basic .NET, resulting in efficient CSV exports.
Performance Enhancement in SQL Server: Optimized SQL Server performance
to handle large queries with minimal resource utilization.
High-Security Environment Expertise: Operated effectively in a highly secure environment
where access was restricted to Excel, SQL, and network folders.
RDLs and Power BI Report Server: Proficiently utilized RDLs (Report Definition Language) and Power BI Report Server
to generate daily reports and dashboards in Excel format.
Efficient Time Management: Successfully managed over 50 periodic tasks,
meticulously organized in a calendar, ensuring timely completion.
Geothermal Plant Designer
08-2023/02-2024
CHEC Grupo EPM
Utilized pivot tables and Tableau to summarize critical inventory and cost information.
Effectively compared various project alternatives.
Designed distribution and transmission networks for connecting the geothermal power plant to the national grid (SIN).
Conducted technical reviews of electrical connection elements, including single-line diagrams.
Performed calculations related to regulation, losses, and inventory.
Developed a complete financial model for the project. Evaluated project viability using metrics such as NPV, IRR, and LCOE.
Calculated the weighted average cost of capital (WACC) effectively. Considered five distinct sources of capital expenditures (CAPEX).
Georeferenced structures and optimized the existing medium-voltage network.
Utilized AutoCAD, Google Earth, and PLS-CADD to efficiently locate support structures.
Ensured compliance with safety distances specified by RETIE (Colombian electrical code).
Employed descriptive and machine learning models, including the powerful LightGBM model.
Engineered relevant features for accurate price predictions in the energy market.
Investment Performance: Achieved outstanding investment results, consistently outperforming the S&P500 with an annual effective return of 28.22% over the past four years.
This performance underscores the stability and rapid growth potential of my portfolio.
Risk-Reward Optimization: Demonstrated proficiency in optimizing risk-reward trade-offs by combining Markowitz’s efficient frontier theory, Python programming, and cross-validation techniques.
These efforts ensure the optimal allocation of asset weights.
Advanced Python Skills: Leveraged Python for finance to consume financial data via APIs
and fine-tune asset weights for optimal returns.
Kaggle Competition Success: Awarded the silver medal in the Kaggle competition “Optiver Trading at the Close.” Employed powerful time series forecasting models, feature engineering pipelines,
and tools such as Pandas, Polars, LightGBM, and Optuna to achieve precise results.
Financial Accounting Expertise: Proficiently interpreted key metrics from balance sheets, income statements, and cash flow reports. Familiar with indicators
including ROE, ROA, current ratio, and price ratios (e.g., PER, EV/EBITDA).
Corporate Governance and Financial Mathematics: In-depth knowledge of corporate governance practices, present and future values,
depreciation, contingencies, and financial mathematics.
Developed a winning stock options strategy by selecting those with the best risk-reward ratio. Created a Python program to automate the process of identifying the optimal options to buy.
Machine Learning Contributor
09-2023/01-2024
Kaggle
Attained a silver medal in Optiver Trading at the Close competition, showcasing
proficiency in algorithmic trading strategies.
Conducted forecasting of 200 stock prices using a vast dataset, demonstrating
expertise in financial data analysis and prediction.
Designed and implemented a comprehensive feature engineering, training, and
inference pipeline on Kaggle, optimizing model performance and accuracy.
Conducted fine-tuning of LightGBM, a leading model for tabular data, to achieve
superior predictive performance in various domains.
Trained LLM models, including the Deberta V3 transformer, for advanced natural
language processing tasks, exhibiting proficiency in cutting-edge deep learning
techniques.
Demonstrated strong proficiency in feature engineering principles and the
determination of feature importances, enhancing model interpretability and
performance.
Possess a robust understanding of time series forecasting methodologies, enabling
accurate prediction and analysis of sequential data patterns.
Proficiency use of TensorFlow, Keras, Sklearn and pyTorch APIs.
Developed AI for image labeling and segmentation using transformers for computer vision.