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Mizan Institute Of Technology

Python Data Science & Al Trainer at Mizan Institute Of Technology


Position Title: Python Data Science & Al Trainer
Employer: Mizan Institute Of Technology
Employment: Full-Time | Permanent
Place of Work: Addis Abeba - Ethiopia
Posted date: 2 weeks ago
Deadline: Submission date is over


About the job

Mizan Institute of Technology (MiT) invites an experienced and passionate Python, Data Science, and AI Trainer to join our team as a full-time hybrid member. This role focuses on delivering comprehensive Python programming, AI, and Data Science training from beginner to advanced levels, empowering students with practical skills and industry-relevant expertise.

Major Responsibilities and Roles:

Python Programming Trainer:

  • Deliver engaging, hands-on Python programming training sessions covering fundamentals to advanced concepts, including OOP, data structures, algorithms, and best practices
  • Teach Python frameworks and libraries, including Django, Flask, FastAPI, and automation tools
  • Develop and update course materials, coding exercises, projects, and assessments aligned with industry standards
  • Guide students in building practical Python applications, scripts, and automation projects.Data Science & AI Trainer
  • Instruct a comprehensive Data Science &AI curriculum covering data analysis, visualization, statistical analysis, machine learning, NLP, CV, GenAI, and deep learning

Teach essential data science libraries and frameworks:

  • NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-learn, TensorFlow, PyTorch, and Keras
  • Cover the complete data science pipeline: data collection, cleaning, exploration, feature engineering, model building, evaluation, and deployment. Provide hands-on training in SQL, database management, and big data tools (Apache Spark, Hadoop basics)
  • Teach machine learning algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers)
  • Guide students through real-world data science projects and Kaggle-style competitions
  • Provide expert mentoring in portfolio development, helping students create industry-ready data science projects.

Skills and Qualifications Needed:

Technical Skills:

  • Expert-level proficiency in Python programming (beginner to advanced).

Deep understanding of Python frameworks:

  • Django, Flask, FastAPI, and web scraping tools (BeautifulSoup, Scrapy)

Strong expertise in data science libraries:

  • NumPy, Pandas, Matplotlib, Seaborn, Plotly, and Scipy.
  • Extensive knowledge of machine learning frameworks:
  • Scikit-learn, XGBoost, LightGBM.

Proficiency in deep learning frameworks:

  • TensorFlow, Keras, and PyTorch
  • Solid understanding of statistics, probability, linear algebra, and calculus for data science.
  • Experience with SQL, database management (PostgreSQL, MySQL), and NoSQL databases (MongoDB).
  • Knowledge of big data tools (Spark, Hadoop) and cloud platforms (AWS, Google Cloud, Azure).
  • Familiarity with MLOps, model deployment, and production pipelines.

Soft Skills:

  • Excellent communication, presentation, and teaching abilities with the capacity to simplify complex concepts
  • Strong analytical and problem-solving mindset.Preferred

Qualifications:

  • Master's degree or Ph.D. in AI, Computer Science, Data Science, Software Engineering, or related field.
  • Industry certifications (Google Data Analytics, AWS Machine Learning, TensorFlow Developer) are a plus.
  • Proven track record in teaching, training, or corporate coaching in Python and Data Science.
  • Distinct portfolio showcasing data science projects, Kaggle contributions, or research publications.
  • Experience with AI technologies, including generative AI and large language models (LLMs).
  • Active participation in data science communities, hackathons, or open-source contributions.

Practical Experience:

  • Minimum 3-5 years of solid hands-on experience in Python programming and Data Science.
  • Proven track record of completed data science projects spanning various domains (finance, healthcare, e-commerce, etc.)
  • Experience with real-world datasets and end-to-end project implementation.




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