About Business Analysis School

Business Analysis School, founded by multi-award-winning consultant Eno Eka, is a leading global provider of practical, career-transforming training in business analysis, project management, and digital transformation. We have empowered over 100,000 professionals from 90+ countries to excel in their careers and drive meaningful change in organizations worldwide.

 Core Responsibilities

- Curriculum Development: Design, update, and enhance AI training modules aligned with industry best practices and emerging trends (topics may include: AI fundamentals, Generative AI, machine learning for business analysts, GPT applications, data-driven decision making, AI ethics, etc.).

- Instruction & Facilitation: Deliver engaging, interactive online and/or in-person instruction to diverse learners globally.

- Hands-On Training: Guide students through real-world AI use cases, projects, and practical assignments relevant to business analysis and digital transformation.

- Mentorship & Support: Offer guidance, answer questions, and provide career advice to learners throughout their training journey.

- Continuous Improvement: Seek feedback from students and update course content regularly to ensure relevance and excellence.

- Collaboration: Work with the Business Analysis School team to develop new programs, host webinars/workshops, and contribute to the school’s thought leadership in AI and digital transformation.

 Key Performance Indicators (KPIs)

- Student satisfaction and course feedback scores (monthly/quarterly)

- Completion and certification rates (monthly)

- Number of students mentored/supported (weekly/monthly)

- Contribution to new program/content development (quarterly)

- Engagement in community forums, webinars, or events (ongoing)

 What You’ll Do (Weekly, Monthly, Quarterly)

Weekly:  

- Deliver scheduled classes, webinars, and office hours  

- Respond to student questions and provide feedback on assignments  

- Refine lesson materials based on latest trends and learner needs

Monthly:  

- Analyze student progress and suggest improvements  

- Collaborate on new course or content creation  

- Host or contribute to live events, Q&As, or panel discussions

Quarterly:  

- Review and refresh curriculum based on industry updates  

- Present results and new ideas to the leadership team  

- Attend or represent the school at industry events/conferences

 Growth Opportunities

- Advance to Lead Instructor roles

- Opportunity to publish thought leadership content, industry articles, or speak on behalf of Business Analysis School

- Influence the direction of new AI and digital transformation curriculum

 Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Business Analytics, or related field (or equivalent professional experience)

- 2+ years of hands-on AI/ML experience (industry or teaching)

- Demonstrated expertise with AI tools, platforms (e.g., Python/ML libraries, GPT, cloud ML platforms) and their business applications

- Prior experience teaching, mentoring, or presenting technical concepts to non-technical audiences

- Excellent verbal and written communication skills

- Strong organizational and project management abilities

- Passion for empowering others and making complex topics accessible

 Preferred Qualifications

- Experience with business analysis or delivering tech-focused training to business professionals

- Knowledge of the role of AI in digital transformation and business innovation

- Industry certifications in AI, data science, or business analysis (e.g., IIBA, Microsoft, AWS)

 Soft Skills & Values

- Empathetic, patient, and approachable mentor

- Growth mindset and commitment to continuous learning

- High integrity, professionalism, and collaborative spirit

- Enthusiasm for making a positive global impact

 How to Apply

Send your resume and a loom video detailing:

1. Your experience teaching or applying AI in business contexts

2. An example of how you made a complex AI concept understandable for a diverse audience

3. Links to any relevant teaching samples, course content, GitHub, or published work