Fractal Analytics – Imagineer Program | Placement Experience

Company & Role

• Company: Fractal Analytics

• Role: Imagineer Program

• Graduation Batch: 2027

• Branch: Electronics & Telecommunication (EnTC)

• Mode: On-Campus

Recruitment Timeline

• Application: August 2026

• Online Assessment: 1st Week of September 2026

• Interviews: 23 September 2026

• Offer Announcement: 24 September 2026

• Final Verdict: Selected

• Students Selected: 7

1. Online Assessment (OA)

The recruitment process began with an online assessment that tested fundamental concepts, aptitude, and practical SQL skills.

MCQ Section

The MCQs covered:

• Quantitative Aptitude

• Logical Reasoning

• English

• Data Interpretation

• DBMS

• Basic Python

Coding Section

The coding section consisted of 2 SQL queries, focusing on practical database querying and SQL fundamentals.

Preparation Focus: Aptitude, DBMS, Python basics, and SQL.

2. Technical Interview 1 – Approx. 40 Minutes

This was the most technically intensive round. The interviewer focused heavily on my projects, internship experience, technical decision-making, and problem-solving approach.

Project Discussion

I was asked to explain my projects in depth, particularly:

• How the project was designed and implemented

• Why specific technologies and approaches were chosen

• Challenges faced during development

• Possible improvements and future enhancements

• Real-world applications

Internship & AI/ML Discussion

A significant portion of the discussion revolved around my internship project involving AI Agents, RAG, and LLMs.

Topics discussed included:

• AI Agents and their architecture

• Retrieval-Augmented Generation (RAG)

• LLMs

• Agentic workflows

• Hallucinations and ways to reduce them

• Evaluation metrics for AI systems

• Scenario-based AI/agent questions

• Designing an AI agent for a given business scenario

Coding & SQL

I was also asked to:

• Write a Python program to find the frequency of a character in a string

• Solve SQL queries

• Explain database concepts

• Discuss evaluation metrics and their practical use

The interviewer also evaluated how I approached unfamiliar scenarios and explained my reasoning.

3. Technical Interview 2 – Approx. 15 Minutes

The second technical round was shorter and focused more on communication, clarity of thought, and high-level technical understanding.

Project Explanation for a Non-Technical Stakeholder

I was asked to explain one of my core projects without going deep into technical terminology.

I discussed:

• The real-world problem being addressed

• Key features of the project

• How the solution helps users

• The overall workflow

• Technologies used at a high level

The interviewer also asked several situational and behavioral questions to understand my:

• Problem-solving approach

• Decision-making

• Adaptability

• Attitude toward challenges

• Communication skills

4. HR Round

The final round was primarily focused on personality, communication, adaptability, and cultural fit.

The interview started with an interesting question:

"Introduce yourself without talking about anything technical."

The discussion then moved toward:

• Situational questions

• Managerial scenarios

• Handling pressure and challenges

• Adaptability

• Teamwork and collaboration

• Professional attitude

• Personal goals and motivations

The conversation was relatively informal and focused on understanding me beyond my technical skills and resume.

Final Verdict

Selected for the Fractal Analytics Imagineer Program – 2027 Batch 🎉

A total of 7 students were selected from the campus drive, and I was one of the 7 selected candidates.

The overall process tested a combination of aptitude, SQL, DBMS, Python, project knowledge, AI/ML concepts, problem-solving, communication, and behavioral skills.

For anyone preparing for a similar role, I would recommend having a strong understanding of everything mentioned on your resume rather than preparing only theoretical concepts. In my experience, being able to clearly explain what you built, why you built it, how it works, and what you would improve was particularly important.