Lucas Griva

Machine Learning Engineer at Pi Data Strategy & Consulting
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Contact Information
us****@****om
(386) 825-5501
Location
Rosario, Santa Fe, Argentina, AR
Languages
  • Inglés Professional working proficiency
  • Español Native or bilingual proficiency

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Credentials

  • Advanced SQL for Data Science: Time Series
    LinkedIn
    Dec, 2020
    - Nov, 2024
  • MongoDB Aggregation Framework
    Coursera
    Dec, 2020
    - Nov, 2024
  • NLP with Python for Machine Learning Essential Training
    LinkedIn
    Dec, 2020
    - Nov, 2024
  • Advanced SQL for Data Scientists
    LinkedIn
    Nov, 2020
    - Nov, 2024
  • Analyzing Big Data with SQL (con Honores)
    Coursera
    Nov, 2020
    - Nov, 2024
  • Managing Big Data in Clusters and Cloud Storage (con Honores)
    Coursera
    Nov, 2020
    - Nov, 2024
  • Programa Especializado - Modern Big Data Analysis with SQL
    Coursera
    Nov, 2020
    - Nov, 2024
  • Aprendizaje Automatizado (Machine Learning)
    Facultad de Ciencias Exactas, Ingeniería y Agrimensura
    May, 2017
    - Nov, 2024
  • The Data Science Course 2021: Complete Data Science Bootcamp
    Udemy
    Jan, 2015
    - Nov, 2024
  • Microsoft Certified: Azure Data Scientist Associate
    Microsoft
    Dec, 2021
    - Nov, 2024

Experience

  • Pi Data Strategy & Consulting
    • Argentina
    • Information Services
    • 100 - 200 Employee
    • Machine Learning Engineer
      • Mar 2022 - Present

  • Accenture Argentina
    • Argentina
    • Business Consulting and Services
    • 700 & Above Employee
    • Data Science Analytics Analyst
      • Jun 2021 - Mar 2022

      Encargado de desarrollar e implementar modelos de forecasting para demanda diaria por producto, demanda horaria de órdenes y de ocupación de parking lot en un quick service restaurant. Implementación de prácticas de Machine Learning Operations para entrenamiento y despliegue continuo de la solución en plataforma de Azure Machine Learning. Análisis y cuantificación de efecto halo y canibalización entre productos en un retail store. Trabajo bajo metodologías ágiles. Stack tecnológico: Azure (Azure Machine Learning, Azure Databricks, Azure SQL Server, Azure Data Factory).

  • CCT CONICET ROSARIO
    • Research Services
    • 1 - 100 Employee
    • PhD. Candidate
      • Apr 2015 - Aug 2020

      Using machine learning and time series modelling for 60- and 120 min. ahead prediction of diabetic patients's glycaemia.Using machine learning modelling for classification of diabetic patients according to their controllability. Research and application of different control algorithms for glycaemia regulation. Using machine learning and time series modelling for 60- and 120 min. ahead prediction of diabetic patients's glycaemia.Using machine learning modelling for classification of diabetic patients according to their controllability. Research and application of different control algorithms for glycaemia regulation.

  • Center for Diabetes Technology - University of Virginia
    • Research Internship
      • Oct 2016 - Dec 2016

      Analysis of data from sensors of diabetic patients for subsequent estimation of regression and classification mathematical models for predicting blood glucose. Matlab user. Analysis of data from sensors of diabetic patients for subsequent estimation of regression and classification mathematical models for predicting blood glucose. Matlab user.

Education

  • Universidad Nacional de Rosario - UNR
    PhD. in Engineering, Electronic Engineering
    2015 - 2021
  • Universidad Nacional de Rosario - UNR
    Electronic Engineer, Electronic Engineering
    2009 - 2015

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