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Data science

Data science

I have 9+ years of experience processing data in high volumes and developing data science solutions for the ATLAS Collaboration


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  • Performed several data analyses comprising:

    • Data preparation and cleaning

    • Precision measurements of physical quantities

    • Various statistical analyses:

      • Extraction of data-driven corrections

      • Determination of uncertainties

      • Test statistic based on profile likelihood ratio for hypothesis testing

      • Chi-square goodness of fit test for hypothesis testing

    • Successfully edited and published 5 scientific results

  • Implementation and deployment of a neural network to predict the position of a particle in a detector:

    • Improved previous estimation by up to 60%

    • Using NumPy, Pandas and Keras from tensorflow

  • Training and optimized an attention-based model to identify physical particles:

    • Improved performance by up to 50%

    • Using Docker and Kubernetes (Kubeflow pipelines and Katib)

Technical skills

Software development:

  • Python for data modeling (Pandas and NumPy), data visualization (Matplotlib and Plotly), automated testing (Pytest) and machine learning and statistical methods (SciPy, statsmodel, Keras from tensorflow, Scikit-learn)

  • Business Intelligence / Analytics tools: Tableau and Looker Studio

  • Git [GitLab and GitHub] and Continuous Integration

  • Docker

  • Kubernetes [Kubeflow]

  • SQL

  • Jupyter notebook

  • Microsoft Excel and Google Sheets




More about me

Project manager

Project Manager

Software developer

Software Developer



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