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Matias Javier EndrekMJ

Matias Javier Endrek

Data Scientist | Python, SQL & Power BI | Machine

€131/day
Córdoba, AR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Matias Javier

I am a data scientist specializing in data analysis, machine learning model development, and business intelligence dashboard creation.

I primarily work with Python, SQL, and Power BI to transform data into useful information that helps companies make better decisions. I have experience in data cleaning and processing, exploratory analysis, predictive model building, and business-oriented data visualization.

I have worked on data analysis projects, process automation, and interactive dashboard development for various types of organizations, helping to identify patterns, optimize processes, and generate strategic insights.

I am interested in collaborating on projects related to data analysis, Business Intelligence, process automation, trend prediction, and the development of Machine Learning-based solutions.
  • English

    Native or bilingual

  • Spanish

    Fluent

Remote only
Primarily works remotely

Experience

  • Insight Analytics Solutions
    Senior Data Scientist
    TECH
    December 2023 - Today (2 years and 8 months)
    Córdoba, Argentina
    Data Scientist specializing in the development of machine learning-based solutions and advanced data analysis for technology companies and startups.

    Key responsibilities and achievements:

    • Development of predictive models for sales forecasting, churn prediction, and customer segmentation.

    • Implementation of data pipelines using Python, SQL, and data processing tools.

    • Building interactive dashboards for business analysis using visualization tools.

    • Optimization of machine learning models to improve accuracy and reduce computational costs.

    • Collaboration with product and business teams to translate data into strategic decisions.

    Technologies used: Python, Pandas, Scikit-learn, SQL, TensorFlow, Power BI, Tableau, APIs, and data process automation.

    Data Scientist specializing in the development of machine learning solutions and advanced data analysis for technology companies and startups.

    Key responsibilities and achievements:

    • Development of predictive models for sales forecasting, churn prediction, and customer segmentation.

    • Implementation of data pipelines with Python, SQL, and data processing tools.

    • Creation of interactive dashboards for business analysis using visualization tools.

    • Optimization of machine learning models to improve accuracy and reduce computational costs.

    • Collaboration with product and business teams to translate data into strategic decisions.

    Technologies used: Python, Pandas, Scikit-learn, SQL, TensorFlow, Power BI, Tableau, API, and data process automation.
    Data science Microsoft Power BI Python SQL Machine learning
  • DataLab Intelligence
    Data Scientist
    TECH
    March 2022 - December 2023 (1 year and 9 months)
    Buenos Aires, Argentina
    Responsible for analyzing large volumes of data and developing machine learning models to optimize business processes and generate actionable insights.

    Main activities:

    • Cleaning, transforming, and performing exploratory analysis of complex datasets.

    • Developing classification, regression, and clustering models.

    • Creating recommendation systems based on user behavior.

    • Automating reports and analyses using Python scripts.

    • Integrating models into production environments using APIs.

    Key results:

    • 25% improvement in the accuracy of demand forecasting models.

    • 40% reduction in data processing time through pipeline optimization.

    Responsible for analyzing large volumes of data and developing machine learning models to optimize business processes and generate actionable insights.

    Main activities:

    • Cleaning, transforming, and performing exploratory analysis of complex datasets.

    • Developing classification, regression, and clustering models.

    • Creating recommendation systems based on user behavior.

    • Automating reports and analyses using Python scripts.

    • Integrating models into production environments using APIs.

    Key results:

    • 25% improvement in the accuracy of demand forecasting models.

    • 40% reduction in data processing time through pipeline optimization.
  • Digital Metrics Group
    Junior Data Scientist
    DIGITAL AND IT
    February 2021 - February 2022 (1 year)
    Buenos Aires, Argentina
    Participation in data analysis projects and development of statistical models to improve data-driven decision-making.

    Responsibilities:

    • Exploratory data analysis and generation of analytical reports.

    • Development of statistical models and machine learning algorithms.

    • Preparation and cleaning of datasets for model training.

    • Creation of dashboards for visualizing business metrics.

    • Support in user behavior analysis and marketing analytics projects.

    Technologies used:

    Python, Pandas, NumPy, Scikit-learn, SQL, Matplotlib, Power BI.

    Participation in data analysis projects and development of statistical models to improve data-driven decision-making.

    Responsibilities:

    • Exploratory data analysis and generation of analytical reports.

    • Development of statistical models and machine learning algorithms.

    • Preparation and cleaning of datasets for model training.

    • Creation of dashboards for visualizing business metrics.

    • Support in user behavior analysis and marketing analytics projects.

    Technologies used:

    Python, Pandas, NumPy, Scikit-learn, SQL, Matplotlib, Power BI.

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Education

  • Diploma in Data Science
    ICARO
    2024
    En este curso dictado por ICARO, aprendí a usar Scikit Learn, librería esencial para llevar adelante modelos de machine learning. Me introduje en el aprendizaje automático mediante aplicaciones como regresión lineal y clasificación. Empleando algoritmos como KNN y decisión TREES. Implementare modelos avanzados como SVM, redes neuronales, ensambles. Además de técnicas como BAGGING y BOOSTING. Y por último aprendí a dejar disponibles los modelos mediante APIs, además de emplear herramientas de computación en la nube.

Skill set

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