Data Science & AI Trainer Curriculum and Learner Experience

Company: Jivoraa Education Pvt. Ltd.

Brand: Future Next Academy

Location: Udyog Vihar, Gurugram

Work Model: Hybrid

Working Days: Thursday to Monday

Work from Office: Thursday, Friday, Saturday and Monday

Work from Home: Sunday

Weekly Off: Tuesday and Wednesday

Experience: Minimum 3 years

Annual CTC: 4-9 LPA, based on experience and demonstrated expertise

Joining: Immediate or short-notice joiners preferred

About Future Next Academy

Future Next Academy is a UK-focused EdTech start-up developing practical, career-oriented programmes across Data, Artificial Intelligence and other emerging qualified domains.

Our learning experience combines live instruction, structured study materials, practical assignments, portfolio-ready projects and career-focused application. Our learners include working professionals, career switchers and ambitious individuals preparing for technology-driven careers.

FNAs Indian operations and hiring are managed through Jivoraa Education Pvt. Ltd.

About the Opportunity

We are looking for a skilled and learner-focused Data Science & AI Trainer who can take ownership of both academic delivery and learning-content development.

This is not a classroom-only training position. The selected candidate will contribute across the learner journeyfrom creating study materials and delivering live classes to designing projects, conducting assessments, resolving doubts and helping learners develop credible skilled portfolios.

The immediate teaching responsibility will primarily focus on our Data Analytics & Generative AI programme, while curriculum, project and learning-support contributions may extend across FNAs broader Data & AI pathway:

The trainer will also help create and record FNAs free Accelerator programmes, which are being developed to make practical, career-relevant learning accessible to a wider audience.

Key Responsibilities

- Live Training and Classroom Delivery

- Deliver engaging live online classes for the Data Analytics & Generative AI programme.
- Explain technical concepts in a practical, structured and learner-friendly manner.
- Conduct live demonstrations, coding exercises, tool walkthroughs and case-study discussions.
- Adapt teaching methods for learners from different educational and professional backgrounds.
- Prepare session plans and ensure every class meets the intended learning outcomes.
- Maintain high standards of learner engagement, attendance and participation.

- Curriculum and Study-Material Development

- Create and continuously improve lesson plans, presentations, study notes, practical exercises, notebooks and supporting learning resources.
- Convert complex technical topics into clear, structured and application-focused learning material.
- Review curriculum content to ensure it remains current, accurate and aligned with industry requirements.
- Develop trainer guides, learner handouts, practice datasets and revision resources.
- Work across relevant topics in data analytics, data science, machine learning, generative AI, automation and AI applications.
- Maintain consistent academic quality, terminology and presentation standards across learning materials.

- Projects, Assignments and Assessments

- Design practical assignments, quizzes, tests, case studies and capstone projects.
- Create clear project briefs, evaluation criteria, submission guidelines and grading rubrics.
- Develop projects using realistic business scenarios and industry-relevant datasets.
- Evaluate learner submissions and provide specific,



constructive and timely feedback.
- Conduct periodic assessments to measure conceptual understanding and practical application.
- Identify learning gaps and recommend appropriate improvement plans.

- Learner Mentorship and Doubt Resolution

- Conduct structured doubt-clearing and academic-support sessions.
- Respond to learner questions related to concepts, tools, assignments and projects.
- Guide learners who require additional academic support without completing their work on their behalf.
- Track learner progress and proactively identify individuals who may be falling behind.
- Support learners in developing technical confidence and independent problem-solving ability.
- Coordinate with internal teams to resolve academic concerns and improve the overall learner experience.

- Portfolio and Career-Project Support

- Help learners select, structure and improve portfolio-ready projects.
- Guide learners in documenting their work through GitHub repositories, dashboards, project reports and case-study presentations.
- Support learners in communicating the business problem, technical approach, insights and outcomes of each project.
- Review learner portfolios for clarity, completeness, technical credibility and professional presentation.
- Conduct project-presentation sessions and provide feedback on both technical work and communication.
- Help ensure that every learner finishes the programme with demonstrable evidence of applied skills.

- Free Accelerator Programme Production

- Help design short, practical Accelerator programmes for free public access.
- Develop scripts, presentations, demonstrations, exercises and downloadable resources for recorded lessons.
- Present and record structured educational videos with clarity and confidence.
- Work with the content and production teams to ensure recordings are accurate, engaging and professionally delivered.
- Review recorded content and support necessary corrections or re-recordings before publication.

- Academic Quality and Programme Improvement

- Collect and analyse learner feedback to identify opportunities for improvement.
- Regularly review assignments, assessments and learning resources for accuracy and relevance.
- Contribute ideas for new projects, learning formats, workshops and learner-support initiatives.
- Maintain organised versions of academic resources and ensure approved content is uploaded correctly.
- Help establish scalable academic processes as Future Next Academy grows.

Required Technical Knowledge The candidate should possess strong practical knowledge across most of the following areas:

- Python for data analysis
- SQL and database fundamentals
- Microsoft Excel and Advanced Excel
- Power BI and/or Tableau
- Statistics and exploratory data analysis
- Data cleaning, transformation and visualisation
- Machine learning fundamentals
- Generative AI concepts and applications
- Prompt engineering
- Large language models and AI-assisted workflows
- APIs, notebooks and practical project development
- Git and GitHub fundamentals

Exposure to tools or concepts such as Streamlit, RAG, LangChain, AI agents, workflow automation or cloud platforms will be an advantage.

Candidate Requirements





- Minimum three years of relevant experience in data science, data analytics, artificial intelligence, technical training or curriculum development.
- Previous experience delivering live technical classes, workshops or corporate training.
- Strong practical command of Python, SQL, analytics tools and data-science fundamentals.
- Working understanding of generative AI and its practical business applications.
- Experience creating structured study materials, presentations, assignments or technical projects.
- Ability to explain complex concepts clearly to learners from non-technical backgrounds.
- Strong spoken and written English communication skills.
- Confidence in presenting and recording educational content on camera.
- Strong learner-management, feedback and problem-solving capabilities.
- Ability to work independently and manage multiple academic responsibilities.
- Comfortable working in an early-stage, fast-evolving EdTech environment.
- Bachelors or masters degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering or another relevant discipline.

Preferred Candidate Profile

Preference will be given to candidates who have:

- Experience working with an EdTech organisation, training institute, university or corporate learning team.
- Experience teaching working professionals or career switchers.
- Developed complete courses, modules or structured learning programmes.
- Designed industry-focused projects and evaluation frameworks.
- Supported learners in creating GitHub, analytics or data-science portfolios.
- Recorded technical courses, tutorials or educational videos.
- Relevant technical or trainer certifications.
- Practical industry experience in addition to teaching experience.

Who Will Succeed in This Role?

This chance is best suited to someone who:

- Enjoys both teaching and building the learning experience behind the classroom.
- Can move comfortably between curriculum creation, live delivery, assessments and learner mentoring.
- Takes ownership of quality rather than waiting for detailed instructions.
- Values practical learning and believes that learners should build, demonstrate and explain their work.
- Wants to join an early-stage education venture where their contribution will directly shape programmes and academic processes.

Why Join Future Next Academy?

- Join an early-stage UK-focused EdTech start-up and help shape its academic foundation.
- Take meaningful ownership across curriculum, teaching, projects and learner outcomes.
- Work across rapidly developing areas including Data Analytics, Generative AI, Machine Learning, Agentic AI and automation.
- Build programmes and academic systems that will evolve as the organisation scales.
- Gain direct visibility and strong long-term growth potential within the academic function.
- Follow a defined five-day schedule with Tuesday and Wednesday fixed off and Sunday work from home.

Selection Process

Shortlisted candidates may be asked to complete:

1. An initial HR and profile discussion.
2. A technical interview.
3. A short demonstration class.
4. A sample curriculum, assignment or project-design task.

Candidates are encouraged to share any relevant teaching samples, recorded sessions, GitHub profile, course materials or project portfolio with their application.

How to Apply

Interested candidates can apply through the relevant job portal or email their updated CV to [email protected].

Please use the subject line:

Application Data Science & AI Trainer

📌 Data Science & AI Trainer : Curriculum and Learner Experience (Gurugram)
🏢 Jivoraa Education
📍 Gurugram