MERYEM MAHMOUD

Eager and motivated data scientist with a strong foundation in artificial intelligence, seeking a junior data science position to apply my skills, drive for challenges, and further enhance my expertise.

Work Experience:

• Muffin. Data Science Intern (Feb 2023 – Aug 2023, Berlin, DE)
  • Collaborated on the implementation of large language models using Langchain for natural language understanding.
  • Collected and analyzed user data for behavioral and demographic insights
  • Utilized Beautiful Soup for blog scraping, extracting valuable insights from unstructured text data
  • Applied advanced NLP techniques, including keyword extraction, and guided LDA for topic modeling.
  • Developed a high-performance hybrid filtering blog recommendation system using synthetic data and light-fm.
• HUAWEI. Data Analyst Intern (Jul 2022 – Aug 2022, Tunis, TN)
  • Built a webapp dashboard using Pydeck and Folium to analyze atmospheric duct impact on TDD network, reducing manual reporting time by 10 hours per week.
  • Aggregated and cleaned unstructured data from 20+ sources, enabling data-driven decision-making.
• TUNISIE TELECOM. Customer Service Center Intern (Jul 2021, Tunis, TN)
  • Assisted in network configurations, contributing to improved network performance.
  • Analyzed the architecture of various services offered by Tunisie Telecom, gaining insights into telecommunications systems.
• Freelance Experience. Graphic and UI/UX Designer
  • Conducted user research and collaborated with developers, resulting in user-centered design solutions.
  • Designed print materials, social media campaigns, and brand identity assets, enhancing brand recognition using Adobe Creative Suite.

Projects:

• Segmentation of Colorectal Cancer Histology Slides (Feb 2022)
  • Reviewed scientific papers, codes, articles, and other documents related to colorectal cancer and medical imaging
  • Developed deep learning models using Mask RCNN and U-Net to detect and segment cancer cells in images from the EVICAN dataset, achieving 90% accuracy.
  • Implemented a supervised learning model for cell classification, increasing accuracy by 15% through feature engineering and ensemble learning.

Education:

• Master of Engineering, National Institute of Applied Science and Technology, Tunis, TN (2023)
  • Major: Computer Networks and Telecommunications
  • Minors: Computer Vision
  • Relevant Coursework: Data Analysis, Artificial Intelligence, Big Data, DevOps, Networks and Telecommunications, Software Engineering, Algorithms and Data Structures, Advanced NLP and Computer Vision.
• Baccalaureate in Computer Science, Said Bou Bakker High School, Monastir, TN (2017)
  • Score: 16.54/20
  • National Rank: 21/6424