Personal Experience
Oumayma is an engineer in statistics and data science, working on a variety of projects. Currently, she excels in her role as a data science consultant. Her competence in artificial intelligence spans several key areas, including computer vision, large-scale language models (LLMs), generative AI, natural language processing (NLP), in addition to her expertise in statistics and data analysis.
Skills
Soft Skills
Professional Experience
As a BI & AI Analyst at Full Remote Factory, I collect and analyze data to inform strategic decisions, while integrating artificial intelligence solutions to optimize processesAs a BI & AI Analyst at Full Remote Factory, I collect and analyze data to inform strategic decisions, while integrating artificial intelligence solutions to optimize processes
Skills:
BI – LLM – Computer vision – Python – Maching learning
-Develop statistical models to analyze complex data sets.
-Evaluate model performance using appropriate metrics.
-Creation of interactive visualizations to represent trends and patterns in data.
Data cleaning and pre-processing to ensure quality and consistency.
-Optimization of statistical models to improve accuracy and efficiency.
-Development of statistical models to analyze complex data sets.
-Evaluate model performance using appropriate metrics. -Creation of interactive visualizations to represent trends and patterns in data.
Data cleaning and pre-processing to ensure quality and consistency.
-Optimization of statistical models to improve accuracy and efficiency.
-Preparation of detailed reports on the results of analyses carried out.
Technical environment:
Statistical modeling – Data visualization – Data analysis
Project: Car Identification for Parking Security
-Gathering of a diverse dataset of car registration numbers for model training.
Integration of parking lot security camera data to reflect real-life conditions.
Statistical modeling:
-Development of a matrix detection model based on computer vision techniques.
-Use of image processing algorithms to extract and recognize vehicle registration numbers.
-Regular evaluation of model performance with validation data sets.
-Integration of the detection model into the parking lot security system.
Implementation of alert mechanisms to signal detected intrusions.
Extensive testing and fine-tuning to ensure reliable performance in real-life conditions.
Technical environment:
Agile methods – Computer vision – Python – Deeplearning
