Data Analytics & Data Science Instructor Job in Nigeria

 Ai Multimedia Academy is the foremost multimedia school in Nigeria and we are committed to excellence in our industry. As we expand, we are seeking a dedicated and experienced individual to join our team and contribute to our success.

We are recruiting to fill the position below:

Job Title: Data Analytics & Data Science Instructor

Location: Ogba-Ikeja, Lagos
Employment Type: Part-Time

Job Description

  • Are you passionate about data analytics and data science? Do you have the expertise to inspire and educate others on the power of data-driven decision-making?
  • If so, we want YOU to join our dynamic team as a Part-Time Data Analytics & Data Science Instructor!

Role and Responsibilities
As a Data Analytics & Data Science Instructor, you will play a crucial role in shaping the next generation of data professionals. Your responsibilities will include:
Curriculum Development:

  • Designing and developing a comprehensive curriculum for data analytics and data science courses.
  • Staying updated with industry trends and integrating real-world applications into the curriculum.

Instruction and Facilitation:

  • Delivering engaging and interactive lectures, workshops, and hands-on exercises.
  • Providing mentorship and guidance to students, fostering a collaborative learning environment.

Project Supervision:

  • Overseeing and guiding students in practical projects, ensuring they apply theoretical knowledge to real-world scenarios.
  • Offering constructive feedback to help students refine their analytical and problem-solving skills.

Stay Current:

  • Keeping abreast of the latest tools, technologies, and methodologies in data analytics and data science.
  • Actively participating in professional development to enhance your own expertise.

Inspire and Motivate:

  • Inspiring students to explore the vast possibilities of data analytics and data science.
  • Motivating learners to think critically, solve problems, and cultivate a passion for continuous learning.


  • Collaborating with the curriculum development team, fellow instructors, and industry professionals to ensure our programs align with industry standards.

Online and/or On-Site:

  • Delivering courses through online platforms and/or in-person sessions based on the needs of our diverse student base.

Student Support:

  • Providing additional support through office hours, one-on-one sessions, and online forums to ensure student success.

Diversity and Inclusion:

  • Creating an inclusive and supportive learning environment that celebrates diversity and fosters equal opportunities for all.

Programming Languages:

  • Python: Widely used for data analysis, machine learning, and statistical modeling.
  • R: Commonly used for statistical analysis and visualization.

Data Manipulation and Analysis:

  • Pandas: Python library for data manipulation and analysis.
  • NumPy: Python library for numerical operations on arrays.

Data Visualization:

  • Matplotlib: Python library for creating static, animated, and interactive visualizations.
  • Seaborn: Built on top of Matplotlib, it provides a high-level interface for drawing attractive statistical graphics.
  • Plotly: Interactive and web-based visualization library.

Statistical Analysis:

  • RStudio: An integrated development environment (IDE) for R, widely used for statistical analysis.
  • Jupyter Notebooks: Interactive web-based notebooks supporting various programming languages, commonly used for Python.

Machine Learning:

  • Scikit-learn: A machine learning library for classical algorithms in Python.
  • TensorFlow and PyTorch: Popular open-source deep learning frameworks.
  • Keras: High-level neural networks API, often used with TensorFlow.

Database and SQL:

  • SQL: Structured Query Language for managing and querying relational databases.
  • MySQL, PostgreSQL, SQLite: Popular relational database management systems.
  • MongoDB: A NoSQL database commonly used for handling unstructured or semi-structured data.

Big Data Technologies:

  • Hadoop: Distributed storage and processing of large data sets.
  • Spark: A fast, in-memory data processing engine for big data processing.

Data Cleaning and Transformation:

  • OpenRefine: An open-source tool for cleaning and transforming messy data.

Version Control:

  • Git: For tracking changes in source code and collaborative development.

Business Intelligence Tools:

  • Tableau, Power BI, Looker: Tools for creating interactive and shareable dashboards.
  • Cloud Platforms:
  • AWS, Azure, and Google Cloud: Cloud platforms that offer a range of services for data storage, processing, and analysis.

Text and NLP Processing:

  • NLTK (Natural Language Toolkit), SpaCy: Libraries for natural language processing in Python.

Collaboration and Documentation:

  • JIRA, Confluence: Tools for project management and documentation.
  • Strong communication skills, both written and verbal.
  • Previous teaching or mentoring experience is a plus.
  • Self-motivated and able to work independently.


  • Flexibility work schedule.
  • Competitive compensation is based on the number of trainees per session.
  • Opportunity to make a real impact on the lives of aspiring coders.

Application Closing Date
31st July, 2024.

How to Apply
Interested and qualified candidates should send their resume, a brief portfolio, and a cover letter outlining their experience and teaching approach to: using the Job Title as the subject of the mail.

Note: Do not attach the proof of your work, only send the link, similarly do not send the link to your CV / Resume, your resume or CV must be sent as an attachment, and your cover letter must be typed in the email body.