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General Information

Full Name Rodolfo José Amancio
Date of Birth 30th June 1994
Languages English, Portuguese, Spanish

Education

  • ongoing
    MsC
    State university of Campinas, Campinas, Brazil
    • Monte Carlo Simulations
    • Statistical mechanics
    • Details
      • Markov chain Monte Carlo algorithms implementations in C, analysis in python
      • Modelling of confined fluids
      • Thermodynamic perturbation terms calculation
  • 2020
    Post-graduate course
    State university of Campinas, Campinas, Brazil
    • Complex data minning
    • Details
      • Information retrieval
      • Data analysis
      • Machine learning
      • Deep learning
      • Big data
    • Progamming languages
      • python
      • R
  • 2018
    Bachelor's degree
    State university of Campinas, Campinas, Brazil
    • Chemical engineering
    • Two times student's monitor (calculus 3 and transport phenomena 3), with scholarship
    • Undegraduate research program in material's engineering, with scholarship
    • One semester abroa at the Royal Institute of Technology (KTH) in Stockhom, Sweden

Experience

  • 2021-
    Data scientist
    Albert Einstein Israelite Hospital, São Paulo, Brazil
    • Development of predictive models, classification and clustering, risk stratification, time series forecasting and statistical analysis, aiming to improve decision-making processes on the management of population health care, based on health determinants.
  • 2021-2021
    Data scientist
    I.Systems, Campinas, Brazil
    • Research and development of predictive models, data clustering, softawre testing and data analysis focused on demand forecast and production planning. The main tools a topics used in my work include, but are not limited to python, AWS (SageMaker, EMR), Power BI, supervised and unsupervised machine learning methods, time series data analysis and forecast, alongside statistics and data analysis.
  • 2018-2020
    Process optimization specialist
    I.Systems, Campinas, Brazil
    • Deployment of advanded process control projects using mainly fuzzy logic, artifficial neural networks, statistical optmization and data intelligence. Another activities included data analysis and modelling, and projects maintenence. These projects have led to processes efficiency improvement, alongside substancial financial gains for the clients.

Academic Interests

  • Probability
  • Statistics
  • Machine learning
  • Causal inference

Other Interests

  • Hobbies: Cinema, literature, music, video-games.