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Alexander Takele

Data scientist

About Me

Data scientist with 5+ years of experience applying machine learning to real-world healthcare and public health challenges. Proven expertise in developing predictive models, fine-tuning large language models, and leveraging explainable AI for actionable insights. I have worked extensively with health data, including the Ethiopian Demographic and Health Survey and Ethiopian Public Health Institute datasets, collaborating with public health experts on research projects addressing childhood immunization, infectious disease outbreaks, and patient care optimization. Passionate about using AI and data science to improve global health outcomes, I seek opportunities to contribute to innovative research that bridges data science and healthcare.

IT Management
95%
Web Development
98%
Network Security
95%
Platform Integration
90%

Education Background

Education & Training

  • MSc in Data Science, University of Gondar, Ethiopia (2019–2022)
  • BSc in Information Science, University of Gondar, Ethiopia (2015–2018)
  • AI & Machine Learning, 10 Academy, Addis Ababa, Ethiopia (Dec 2023 – Jun 2024)
  • Back-End Development, ALX Holberton School, Addis Ababa, Ethiopia (Mar 2022 – Jul 2023)

Skills & Expertise

  • Programming & Databases: Python, JavaScript, C++, SQL, MongoDB, Postgres, ChromaDB, FAISS
  • Data Analysis & Modeling: Pandas, NumPy, Matplotlib, Seaborn, Jupyter, Tableau, Power BI, Regression, Clustering
  • Data Engineering: EDA, ELT/ETL, Airflow, DBT, Redash, Data Modeling & Visualization
  • ML & Tools: TensorFlow, PyTorch, Scikit-learn, Hugging Face, Transformers, Spark, Hadoop, Git, AWS, Heroku, Docker
  • Geometry Optimization: Graph-based ML, Geometric Deep Learning, 3D Reconstruction, Numerical Methods
  • Soft Skills: Communication, Teamwork, Problem-Solving, Analytical Thinking, Attention to Detail

Work Experience

Data Analyst, Gondar Comprehensive and Specialized Hospital (Feb 2023 – Feb 2024)

  • Built ML models for hospital operations, including patient stay prediction (98.97% accuracy)
  • Analyzed EPHI data on child immunization using XGBoost (93% accuracy)
  • Predicted under-five diarrhea risk from national survey data using CatBoost (94.79% accuracy)
  • Delivered machine learning training sessions to health professionals

Lecturer & Researcher, University of Gondar (Nov 2022 – Present)

  • Teach Machine Learning, Python, and Database Management
  • Enhanced student projects, boosting internship placements by 30%
  • Developed ML and software curricula aligned with industry standards
  • Led data science service projects benefiting local organizations

Research Interests

Geometric Deep Learning, 3D Computer Vision, Large Language Models (LLMs), Explainable AI, Fairness in Machine Learning

Certifications & Online Courses

  • Intro to Transformative AI, BlueDot (Feb 2025)
  • Data Analysis Fundamentals, Udacity (Jul 2024)
  • Machine Learning for Data Science and Analytics, IBM (May 2022)
  • Cloud Computing Fundamentals, IBM (May 2022)

Projects & Publications

  • Telecom User Analytics with ML Pipelines – Medium
  • Contract Advisor Chatbot with RAG & LLMs – Medium
  • Tomato Disease Detection with Transfer Learning & XAI – GitHub
  • Published:
    • IPV Prediction in Ethiopia (DOI: 10.1186/s12911-022-01992-6)
    • Routine Immunization Status Prediction (DOI: 10.21203/rs.3.rs-1445740/v1)

Grants & Leadership

  • Project Lead: AI-Based NEET Risk Assessment for Gondar City (2024, Funded by UoG)
  • Co-Lead: ML for Infectious Disease Outbreak Prediction in Gondar (2024, Funded by UoG)