Federico Martin
Data Scientist
I’m a enthusiastic Data Scientist with engineering background (Chemical Engineering) driven and focused on finding those experiences that build character and enrich ones career. Currently working as a Data Scientist in finance field, executing artificial intelligence solutions to increase efficiency, accuracy and utility of data (recommendation systems, churn models, etc.).
My complete projects of Data Science
Experience developing Churn Models to predict customer retention in financial business structure. Considering diverse features and using ensemble models.
A recommender system for customers, based in their behavior with implicit data. Modern algoritms such SCD++ from scikit-surprise library.
Customer segmentation using K-means from Scikit-learn library, comparing general population data and customer population data.
Reporting and dashboard making using PowerBI, for a wide range of data type: such data from customers, human resources and revenues.
Neural network prototype for recognition of flower images, using TensorFlow.
Grade: Machine Learning with TensorFlow Project-based course about machine learning techniques used in data science: Supervised Learning, Deep Learning and Unsupervised Learning (Clustering).
Machine learning. Time series analysis. Jupyter Lab. Python programming. Libraries: Pandas, Matplotlib, Seaborn, ScikitLearn, Numpy, StatModels.
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Grade: Chemical Engineering This degree aims of addressing the integral development of process plants industrial projects, applying their academic and professional background and expertise to the performance of feasibility studies, environmental impact assessment, design, estimation, construction, installation, operation as well as devising and tracking of production and commercialization plans.