Faculty – Data Science Fresher Job: IAER Kolkata

 Faculty – Data Science Fresher Job: IAER Kolkata – Reality Check Before Applying

Nowadays, you’ll see one Faculty - Data Science Fresher Job after another on LinkedIn, Internshala, and WhatsApp groups—especially from private institutes in Kolkata. This IAER Kolkata job post clearly falls into that same category.

But the real question is—what is the actual objective of this Faculty - Data Science Fresher Job?

On paper, the job description sounds very academic-friendly. But what does the work really look like in practice?

This blog is not a promotion. Here, I will clearly explain:

• What this Faculty - Data Science Fresher Job is actually about
• Who can realistically survive and grow in this role
• Which AI tools you must know to avoid problems
• How to prove your experience in your CV
• And why I explain these types of AI jobs separately

 What is the real objective of this Faculty – Data Science Fresher Job?

The main objective of this Faculty - Data Science Fresher Job is not research and not building advanced AI models.

Institutes like IAER primarily focus on:

• Teaching students industry-oriented Data Science skills
• Following the MAKAUT syllabus and preparing students to pass
• Making students placement-ready

So, in this Faculty - Data Science Fresher Job, your role becomes teacher + trainer + mentor—all at once.

The expectations are clear:

• You must understand the syllabus and explain it properly
• You should use real-life examples to make concepts clear
• You should not get stuck when students ask questions

If you think this Faculty - Data Science Fresher Job is only about showing PPT slides, the reality is very different.

 What kind of work will you actually do in this role?

Daily work in a Faculty - Data Science Fresher Job usually looks like this:

 Classroom Teaching

• Python basics, Pandas, NumPy
• Statistics for Data Science
• SQL queries (SELECT, JOIN, GROUP BY)

 Practical / Lab Sessions

• Running code in Jupyter Notebook
• Explaining basic ML models using datasets
• Creating charts in Power BI or Tableau

 Project & Internship Guidance

• Suggesting final-year project topics
• Mini projects using Kaggle-style datasets
• Checking internship reports

 Academic Support

• Setting question papers
• Evaluating answer sheets
• Participating in syllabus update discussions

This Faculty - Data Science Fresher Job is not narrow like a corporate role. You need to handle a bit of everything.

 Who is this job really for?

This Faculty - Data Science Fresher Job is not for every Data Science learner.

 This job is for you if:

• You can clearly explain concepts
• You know coding but don’t want pure corporate pressure
• You have patience for teaching
• You don’t get irritated by basic student questions

 This job is NOT for you if:

• You only want a high-paying ML engineer role
• Your main goal is publishing research papers
• You dislike classroom environments

Simply put, this Faculty - Data Science Fresher Job is an academic career starter role.

 Which AI tools will you use in this job?

Many freshers think faculty jobs are only about books. In reality, this Faculty - Data Science Fresher Job heavily depends on AI tools.

 Common Tools:

• Python (Anaconda, Jupyter)
• ChatGPT – for concept explanation and assignment design
• Power BI / Tableau – for data visualization
• Google Colab – for ML demonstrations
• Excel – for statistics and analysis

Using ChatGPT in this Faculty - Data Science Fresher Job is not cheating—it’s smart teaching support.

 Ask yourself these 3 questions 

Before applying, you must ask yourself these three questions:

• Which AI tools will I use in this job?
• Have I used these tools before?
• Can I prove this experience in my CV?

If these answers are not clear, this Faculty - Data Science Fresher Job can become risky for you.

 How can you prove your experience in your CV?

Shortlisting for this Faculty - Data Science Fresher Job is proof-based.

Add these to your CV:

• Mini teaching demos (YouTube or Drive links)
• Student project mentorship experience
• Power BI dashboard screenshots
• GitHub repositories with basic ML projects

If you only list certificates, it sends a weak signal for this Faculty - Data Science Fresher Job.

 How should you prepare before applying?

Preparation for a Faculty - Data Science Fresher Job is not a coding marathon.

Smart preparation:

• Pick one topic and practice explaining it
• Revise Python basics
• Understand one ML algorithm end-to-end
• Build one Power BI dashboard

With this preparation, your interview confidence will be much higher.

 Salary & Job Benefit Reality

The salary in a Faculty - Data Science Fresher Job is not like corporate roles.

Benefits include:

• A stable start to an academic career
• Real teaching experience
• Opportunities for research
• Building an industry and academic network

For those planning a long-term academic path, this Faculty - Data Science Fresher Job is an investment.

 Why do I explain these AI jobs separately?

Because not all AI jobs are the same.

Many freshers apply for this Faculty - Data Science Fresher Job with the wrong expectations—and later feel disappointed.

Knowing the reality helps to:

• Stop wrong applications
• Select the right candidates
• Reduce long-term career damage

That’s why I explain this type of Faculty - Data Science Fresher Job separately.

Conclusion

The IAER Kolkata Faculty - Data Science Fresher Job is:

• A coding + teaching hybrid role
• Fresher-friendly but responsibility-heavy
• A genuine academic career starter

Apply only if you are mentally prepared for teaching.

👉 Don’t apply blindly. Understand the reality and decide wisely.  

Interested candidates may share their CV at: career@iaer.ac.in  

Apply Now

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