↓Skip to main content

Resume

English
Victor Coscrato

Victor Coscrato

PhD in Artificial Intelligence

Education #

  • Ph.D in Artificial Intelligence (2019 – 2024) – University College Cork, Ireland.
  • Master in Statistics (2018 – 2019) – Universidade Federal de São Carlos / Universidade de São Paulo, Brazil.
  • Bachelor in Statistics (2014 – 2017) - Universidade Federal de São Carlos, Brazil.

Work experience #

  • FI GROUP (09/2024 – Current): Data science Analyst

    • Lead the end-to-end development and deployment of AI products to enhance consultancy operations, including solutions integrating Large Language Models (LLMs). Responsibilities encompassed full-stack development, designing intuitive frontends (UI/UX), building robust backends with seamless database and ML/AI model integration, and ensuring production-ready deployments.

  • KEELVAR, CORK – IRELAND (04/2021 – 08/2021): AI/ML Analyst

    • Design and implementation of an end-to-end supplier recommender system.

  • STONE PAGAMENTOS SA, BRAZIL (06/2017 – 12/2017): People Analytics Analyst

    • Responsible for automating the selection of candidates in selection processes.
    • Creation of metrics and models for employee evaluation.

Skills #

  • Extensive knowledge of various fields of artificial intelligence: Recommendation Systems, Computer Vision, Natural Language Processing (NLP), Deep Learning (DL), People Analytics.
  • Vast knowledge in statistical modeling: Linear/Logistic regression and classification, Neural networks, Random Forest, SVMs, Ensembles, etc.
  • Experience in developing innovative AI solutions utilizing large language models (LLMs).
  • AI/ML/Statistics Tools and Libraries:
    • Python and its AI/ML ecosystem: PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, PySpark, XGBoost, OpenCV, etc.
    • R and its analytics and statistical modeling tools: Tidyverve (dplyr, tidyr, tibble, purrr, tidymodels, etc.), Caret, mlr3.
    • Data Visualization Tools in Python and R: Matplotlib, seaborn, ggplot2.
  • AI in Production – Tools and technologies for deployment and scaling:
    • Docker, Kubernetes for containerization and orchestration.
    • SQL, MongoDB for database integration in AI workflows.
    • APIs (e.g. FastAPI) for serving AI models in production environments.
    • Cloud platforms: Google Cloud, Amazon AWS, Microsoft Azure.

Research #

See my research papers in this Link ↗️