The posting
About Us
Simplilearn is the world’s #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialized training offered in partnership with world-renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, and more — that are transforming the global economy. Our training is hands-on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2000 corporate training organizations across 150 countries have harnessed our award-winning programs to achieve their career and business goals.
Simplilearn has collaborated with Fullstack Academy to leverage its widespread footprint in the US region and partnerships with Top US universities to grow internationally.
Position Overview
The Part-Time Instructor for Generative AI in Data Analytics plays a key role in delivering engaging and impactful learning experiences to adult learners enrolled in our online programs. Instructors facilitate curriculum content, support student learning, and connect Generative AI concepts with real-world analytics and business intelligence applications. This role involves teaching live online sessions, mentoring learners, providing feedback, and contributing to a collaborative instructional environment. Classes are delivered 100% online in a synchronous format.
Key Responsibilities
Deliver live online training sessions on Generative AI applications in analytics.
Cover key topics including:
Generative AI in Analytics
- Overview of Generative AI in data analytics
- Role of AI in modern analytics workflows
- Emerging trends and enterprise applications
AI-Driven Data Analysis
- Data augmentation using AI-generated synthetic data
- Generative AI for exploratory data analysis
- AI-assisted data interpretation and insight generation
- AI-driven data modeling and forecasting concepts
AI-Powered Visualization & Reporting
- Generative AI for tailored data visualization
- AI-assisted dashboarding and reporting workflows
- Integration of AI into visualization pipelines
AI & Data Engineering Workflows
- Optimization of ETL processes using AI tools
- AI-assisted workflow automation concepts
- Data preparation and transformation using AI-enabled tools
Ethics & Future Trends
- Challenges and ethical considerations in integrating AI into analytics workflows
- Responsible AI usage and governance concepts
- Future trends and emerging applications in AI-driven analytics
Provide hands-on demonstrations using relevant AI and analytics tools.
Facilitate practical exercises, case studies, assignments, and project guidance.
Mentor learners and resolve technical or conceptual queries.
Conduct assessments, evaluations, and feedback sessions.
Maintain session quality metrics, learner engagement, and reporting standards.
Collaborate with internal teams on curriculum refinement and content enhancement initiatives.
Required Qualifications
- Bachelor’s degree in Data Science, Analytics, Computer Science, Artificial Intelligence, or related field
- Industry experience applying Generative AI or AI-assisted analytics techniques
- Strong understanding of data analytics workflows and tools
- Familiarity with LLM-based tools, prompt engineering, or AI platforms
- Prior experience delivering online or classroom training preferred
- Excellent communication, facilitation, and presentation skills
- Ability to explain AI concepts through practical analytics use cases
Preferred Skills
- Experience with Python, SQL, or analytics ecosystems
- Exposure to AI platforms and tools such as:
- OpenAI’s ChatGPT
- OpenAI Playground
- Hugging Face
- Similar Generative AI platforms and LLM ecosystems
- Experience integrating AI into visualization, reporting, or analytics pipelines
- Certifications in AI, Data Analytics, or Data Science
- Familiarity with AI-assisted automation and business intelligence workflows
Key Competencies
- Ability to bridge AI concepts with practical analytics use cases
- Strong learner engagement and facilitation capability
- Structured and professional virtual delivery approach
- Analytical and mentoring mindset
- Strong problem-solving and communication skills
- Adaptability to evolving AI technologies and analytics trends
Student Support & Mentorship
Provide individualized student support during live sessions and scheduled office hours.
Maintain regular communication with students regarding progress, expectations, and milestones.
Respond to student and staff communications in a timely and professional manner.
Provide clear, constructive, and timely feedback on assignments, assessments, and projects.
Performance Monitoring
Evaluate student progress based on course deliverables and established grading rubrics.
Maintain accurate documentation of student performance and engagement.
Identify and escalate academic or learner performance concerns to the Lead Instructor or appropriate staff.
Support learner improvement plans and project readiness initiatives when necessary.
Collaboration & Professional Conduct
Adhere to institutional policies and instructional team standards.
Foster an inclusive, respectful, and professional learning environment.
Serve as a role model and mentor for learners pursuing AI and analytics careers.
Collaborate with instructional staff and program teams to improve the learner experience and program outcomes.
Represent the organization professionally when interacting with students, staff, and external stakeholders.
Work Schedule
Part-Time instructors typically work 10–15 hours per week depending on cohort schedules.
The total weekly part-time commitment is expected to be 8–12 hours.
Weekday - 06:30 PM CST - 09:30 PM CST (Monday, Wednesday and Thursday)
Weekend - 09:00 AM CST - 12:00 PM CST (Saturday and Sunday)
Flexibility for evening availability is required.
Compensation
The anticipated pay range for this position is $55 – $60 per hour, depending on qualifications and experience.
This position is classified as Part-Time, Non-Exempt, and employees will be compensated for all hours worked in accordance with applicable federal and state wage and hour laws.
Equal Employment Opportunity
We are committed to creating an inclusive environment for all employees and applicants. Employment decisions are made without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.
Work Authorization
Applicants must be legally authorized to work in the United States at the time of application and throughout employment.
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