Aircraft Valuation SaaS: Predicting Prices with ML & Big Data

· Tech Objective: Developed a SaaS using Databricks, Apache Spark and Python to predict aircraft prices based on Machine Learning models (Linear Regression, KNN and Random Forest).

· Business Objective: This project enhances decision-making in aviation by leveraging Big Data for accurate, scalable valuations. Over 2,500 aircraft models analyzed to deliver precise insights for industry stakeholders.

Featured Projects.

Enhancing Maritime Efficiency:

Machine Learning in Ship Movements

· Tech Objective: Develop a Python code using data analysis oriented libraries such as Pandas and Numpy, and MatPlotLib for data visualization.

· Business Objective: Enhance the efficiency and safety of maritime operations by accurately predicting vessel behavior in real time.

Recidivism Risk Assessment: A Machine Learning Analysis

· Tech Objective: Utilize COMPAS data with Python tools such as pandas, numpy, and matplotlib for data manipulation and visualization. Apply machine learning algorithms to assess the accuracy of recidivism predictions. Conduct bias detection using statistical fairness metrics

· Business Objective: Evaluate the effectiveness of COMPAS in reducing recidivism and aiding judicial decisions, ensuring fairness across demographic groups.

Telecom Company Business Analysis with Apache Spark

· Tech Objective: Develop a business analysis of a company using Databricks, a service for the analysis of large volumes of data using the distributed computing framework Apache Spark (Cluster of 15.25GB of RAM and 2 cores).

· Business Objective: Perform a complete analysis of a company's customer portfolio to develop a commercial strategy.

About Me.

Senior Big Data & Artificial Intelligence Consultant in Digital Finance.

Data Governance, AI, Cloud Architecture & Engineering

Designed and built scalable solutions using object-oriented programming languages (Python, PySpark, SQL & Scala), with cloud technologies (Amazon S3, Azure Data Lake, Azure Synapse & Snowflake), on premise technologies (IBM DB2, SAP, Oracle) and reporting & visualization software programs (PowerBI).

Financial Analysis, Operations Strategy, Risk & Debt

Worked in risk mitigation strategies, assessment of credit and operational risks, analysis of debt structures and development of strategies to ensure financial stability in complex corporate environments.

Work Experience

Team Leadership

Led the onboarding and follow up of new team members, fostering a collaborative and innovative work environment.

Data Quality & Automation

Engineered cloud-based data quality frameworks and automated database connectivity solutions using Python & PyOdbc, Informatica Developer, Control-M & Erwin Data Modeller.

Ensured continuous integration and code quality through rigorous testing, defect analysis, and version control with Git & Azure DevOps.

B.Sc. in Industrial Engineering: Solid foundation in engineering principles, problem-solving, and technical expertise.

M.Sc. in Data Science and Business Analytics: Specialized in Big Data, Machine Learning, and advanced analytics, with a thesis graded 9.1/10.

Master of Business Administration (MBA): Comprehensive knowledge of business strategy, leadership, and decision-making. With a thesis graded 9.0/10.

Certifications: C1 Advanced English Certification and multiple professional certifications in technology and data analytics.

Education Experience