Naya Homes

I specialize in analyzing real estate data using georeferencing / geospatial techniques applying machine learning and various areas of artificial intelligence.

Through georeferencing, spatial patterns in the distribution of properties are mapped. Through machine learning, predictive models are created that refine price predictions and decision making.

Data Scientist

Applaudo Studios

Appllied AI explained to supervised (Xgboost) and unsupervised (Kmeans) models for infer the best approaches to improve the client's business model with qualitative and quantitative methods.

Implemented Natural Processing Language and topic modelling over thousands comments with the objectives of extract insights and improve processes and policies.

Structured pipelines in Kedro framework (python) and pushed via basic git commands to attlasian repositories.

Machine Learning Engineer

DEV.F

Create content to teach Mathematical Fundamentals classes (Infinitesimal Calculus, Probability and Stochastic Statistics), Introduction to Python (Lists, dictionaries and SQL) and Data Wranglin with libraries like pandas, sklearn and Xgboost.

Study ways to make information as simple and digestible as possible with comprehension techniques such as outlines, graphs, and storytelling.

Teacher of Data Science and Artificial Intelligence

QUASH.ai

Data Scientist in Credit Risk

Create models that increase customer acceptance by more than 15% on average, reduce risk by more than 50% on average, and increase entity profitability by around 25% on average.

Made Feature Engineering, planning, structuring and development of Machine Learning algorithms (Logistic Regression - XGBoost - Neural Networks) for the optimal classification of good and bad payers in credit scoring and credit risk projects, measuring results with metrics such as: ROC Curve AUC and KS.

Estimate the Probability of Default (PD) of rejected customers and make comparisons between customer scores and those of my models to verify performance.

Use qualitative statistical analysis of results and quantitative contribution of customer value, customer segmentation with unsupervised algorithms (Kmeans) and written natural language processing (NLP).

Data Scientist 

Coderhub

Plan and develop a simple neural network model in Keras - Python to classify two classes (0 and 1) in an unbalanced dataset with optimal indicators of recall and precision.

Determine the best model to detect class minority in stress tests with optimal precision and recall.

Structured of algorithms in functions that use the model and automate the process of querying forecasts by date and client for the services in the API.

Data Scientist of Machine Learning , Deep Learning and NLP ( IA )

Freelance Data Scientist

Structuring, development and implementation of a market analysis system with webscraping to obtain data on: prices, location and services, and then segment by region and country.

Data manipulation applying written natural language processing, to extract data determined by a pattern, as well as quantify the impact of the business and/or products (engagement) on customers, measuring the polarity and subjectivity of comments written in English.

Programming of bots for Instagram and twitter in order to send friend invitations, likes and
automatic comments with certain patterns.

Data Scientist in Inteligencia Artificial (Machine Learning Deep Learning y NPL)

KAVAK Mexico

Learned the approach of Extraction, Transformation and Loading of data using integration schemes under environments such as: PostgreSQL and Pentaho, whose interface allowed the manipulation of data, the link of the different tables and the creation and/or deletion of the same.

Structured and development of a product’s recommendation system for the institution's website based on NLP (Natural Language Processing) and implementing content filtering (filter based in content) and knowledge filtering (filter based on Knowledge ) adapted to the needs of the company using tensorflow.

Planning a car demand system implementing: Linear Regression and XgBoost

Bigvene

Development and implementation of algorithms to obtain data from the API of social networks such as: Instagram and Twitter, to determine the structure of the user community, through its characteristics, patterns and perceptions, in order to implement marketing campaigns. marketing through the implementation of Artificial Intelligence and Data Mining.

Abilities:
1.-Programming in Python.
2.- Manipulation of .json Objects

Market Analyst (Data Mining in Social Networks)

Nativa payments (by Banesco Holding Medios de Pago)

Abilities to control and monitor investment projects from a financial point of view applying Business Intelligence criteria (cost-profitability) and project management (execution-time), in addition to carrying out procurement processes and managing the supplier portfolio .

Finance Specialist

Banesco Banco Universal

Financial Analyst assigned to the Energy Banking (Hydrocarbons and Metallurgy), Capital Investments (CAPEX), TDC Issuer Product and TDC Accounting departments, with extensive experience in the banking business applying business intelligence techniques to produce information through the analysis of data through the administration and processing of databases to structure the statistics that allow the realization of the investigation and development of knowledge through the study of the financial risks determined with the purpose of collaborating in the decision-making process decisions.

Financial Analyst

Mi Principal Objetivo es buscar la interpretabilidad de los modelos de Inteligencia Artificial. */ My Principal Objective is to search for the interpretability of Artificial Intelligence models.

Taplio

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