Passionate about steering data integrity through meticulous cleansing and validation processes, I lead a proficient team in leveraging technologies like Python, Databricks, and BigQuery to drive business intelligence projects. My expertise encompasses managing API connections with key partners, overseeing data migrations from Salesforce to proprietary databases, and implementing robust data replication processes. I thrive on maintaining and developing the team's codebase, ensuring seamless, innovative solutions that enhance our data-driven decision-making capabilities.

As a dedicated Data Scientist, I specialize in Python and Databricks to architect and manage a robust data lake, serving as the backbone for our team's business intelligence reporting. My role involves not only the strategic hosting of BI reports but also the meticulous cleansing and validation of data to ensure accuracy and reliability. I am adept at creating insightful reports directly from Salesforce, empowering our team with actionable data insights to drive business decisions.

As an experienced consultant in educational products and services, I focus on enhancing the quality and effectiveness of the Edutec Guide's surveys for teachers and schools. My role involves critically reviewing and improving survey designs to address specific educational needs and objectives. I identify and rectify quantitative issues to ensure data accuracy and reliability. Additionally, I lead pilot tests of the surveys to verify their face validity, guaranteeing that they accurately measure what they are intended to and effectively contribute to the advancement of educational practices.

- Consultancy to train and deploy Machine Learning algorithms for finance industry

- Performed exploratory analysis for Rappi earnings model- Traines Machine Learning models to predict and estimate earnings

- Design specialized training programs in Data Science.- Supervise corporate training courses and programs.

- Formulate an econometric model of fiscal policy and the objectives of Good Living.- Develop a theoretical framework to support the econometric model.- Generate a proposal for fiscal policy to prioritize public spending

- Survey design to collect data regarding teachers' motivation and leadership - Exploratory Factorial Analysis to validate survey- Multilevel modelling to determine factors that influence teachers' motivation and leadership

- Use web scrapping to capture information about hotels and attractions in Ecuador- Build methodology and calculation of Tourism Service Quality Index - Lecture Introduction to Python course

Introductory statistics for engineers.Leading research High-Dimensional Bayesian Vector Autoregression (BVAR) to forecast economical behavior in Ecuador.

Evaluation of statistical operations concerning international entries and exits in cooperation with the Inter-American Bank of Development

Data mining.Machine Learning algorithms applied in risk management problems.Developing R functions and models to evaluate risk of default on High-dimensional data.Unsupervised learning algorithms for market segmentation.

• Macroeconomic modeling• Data Analysis and Cleaning• Quality of Investment Methodologies• Good Living National Plan 2013-2017

- Survey and sampling design to understand living conditions in small Ecuadorian communities- Unsupervised Machine Learning models to reduce dimensions and cluster individuals