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Skills

  • Analytics
  • Data Analysis
  • Data Visualization
  • Machine Learning
  • Mathematics
  • Algorithms
  • Data Management
  • Data Modeling
  • Power BI
  • Python
  • Statistical Analysis
  • Tableau
  • TensorFlow

Services

  • Data Scientist

    $30/hr Starting at $200 Ongoing

    Dedicated Resource

    I am a Data Scientist with experience in Machine Learning to carry out persuasive collection campaigns and attract new clients. I am a very curious data scientist and I love to investigate and learn from...

    AlgorithmsAnalyticsData AnalysisData ModelingData Visualization

  • BI and Data processing ETLs

    $40/hr Starting at $450 Ongoing

    Dedicated Resource

    In Python: 1. Data collection Collecting data is the first step in data processing. Data is pulled from available sources, including data lakes and data warehouses. It is important that the data sources...

    AnalyticsData AnalysisData ManagementData VisualizationMachine Learning

About

I have experience usying of different Machine Learning and Deep Learning tools (PySpark, Scikit-learn, Tensor Flow, NLTK, Pandas among others) to structure collection campaigns

Using neural networks (Tensor Flow in Python), the process of homologation of vehicle brands and lines was automated for the settlement of taxes, reducing the operational load by 75%.
With neural networks (Tensor Flow in Python) and collection campaigns were structured for operations, managing to increase collection between 21% and 33%.
With Python and Pandas, a virtual Supervisor was built for operations that, by identifying the Out Layers (atypical cases), generates alerts to prevent the expiration or prescription of the traffic infraction processes, increasing collection and avoiding fines.
With Phyton, Pandas and Tensor Flow, the customer acquisition campaigns with the highest probability of renewal were structured from tables of 15 million records for the Technical Mechanical Review and SOAT partners.
With Python, Pandas and databases in PosgreSQL, the process of reporting allies, reconciliation and invoicing was automated.
With PySpark, Random forest classifier and NLTK (Natural Language Toolkit) a model was developed to predict with 82% accuracy the candidates who will pass the first stage in a selection process (Hackathon).

Work Terms

Preferably payment per deliverable