Hansika's Jobaaj Learnings Review: From MSc Graduate to Data Analyst at DRRT

"I was actively looking for a full-time role, and even though I had some interview calls, I couldn't get the offer letter until I reached out to Jobaaj." — Hansika

Hansika is from Mumbai. She holds a Bachelor's in Economics and an MSc in Behavioural and Data Science, and completed two internships after her master's. She was getting interview calls but no offers — until she reached out to Jobaaj Learnings. She is now a Data Analyst at DRRT, a legal firm handling confidential shareholder data.

If you are searching “is Jobaaj Learnings genuine”, “is Jobaaj real or fake” or “why am I getting interviews but no offers”, Hansika's case is precisely that last problem. Her account is also refreshingly unvarnished about the outcome: the role is largely Excel work plus administrative tasks written into the contract, and she says plainly that she had wanted to be placed outside Mumbai. Read it alongside the other conversations in our Interview Series and the wider feedback on the reviews page.

Who Is Hansika? Qualified, Interviewing, and Not Converting

Hansika's academic and early professional record is solid:

• Bachelor's in Economics — heavy on statistics
• MSc in Behavioural and Data Science — with a strong data science and analytics focus
• Two internships, taken after a break following her master's

Her move into analytics was, in her words, “a natural progression” rather than a switch — economics gave her the statistics, the MSc gave her the field.

And still:

"I was actively looking for a full-time role, and even though I had some interview calls, I couldn't get the offer letter."

That is a specific and common failure state, and it is different from not being shortlisted. Her profile was getting her in the room; something after that was not closing.

The Role: Excel, and Administrative Tasks in the Contract

Hansika describes her employer plainly: “It's a legal firm that handles confidential data related to shareholders and their dealings.” And her role:

"My role involves uploading raw data, consolidating it, and analyzing it in Excel. There are also some administrative tasks mentioned in the contract that I'll handle as well."

We are keeping that second sentence exactly as she said it, because most placement write-ups would cut it. The job is Excel-based data work plus contractually specified administrative duties. That is a real, paid analyst role in a specialised legal-data domain — and it is not a pure analytics seat. Read it as it is.

Her own summary of the analyst role at the firm: “mainly revolves around handling and analyzing data in Excel.” Three candidates in this series — Hansika, Nisha Saini and Sufiyan Ahmad — independently report that their day-to-day work is one tool, not the full stack they trained on.

The Interview: Four Rounds Across Two Months

Total elapsed: about two months, with the interview phase itself running two to three weeks. The gap between those two figures is waiting — which is where most candidates lose momentum, and where she says the placement team kept the process alive.

She Interviewed at Two Companies, Not Ten

Hansika is precise about volume, and it is lower than most accounts in this series:

"I gave interviews for two companies – DRRT and another company in Bangalore. I didn't consider the third one because I had already received the DRRT offer before the interview happened."

Two interview processes, one offer. That is a very different funnel from Kanishk Goyal's 100–150 applications or Manan Shah's six or seven interviews — and worth noting alongside her own observation that the job market was tight at the time.

The Honest Note: She Wanted to Leave Mumbai

Asked whether being placed in her home city was convenient, Hansika does not simply agree:

"Yes, it's convenient, but I did want to be placed outside the city."

A small line, and the only note of disappointment in the conversation. It is worth surfacing rather than burying: the outcome met the requirement but not the preference. If location matters to you, state it early and ask how it will be weighted.

What the Placement Team Actually Did

Hansika names four specific things, and one of them is unusual:

• Reached out to partner companies — which she frames as mattering “especially when the job market was tight.”
• Rewrote her CV, incorporating her internship experience and, in her words, ensuring it was done professionally.
• Kept the process alive when the employer went quiet. “Even when DRRT took time to respond, the Jobaaj team helped me stay in touch with them.”
• Provided job leads through LinkedIn, simplifying the search.

The third is the one to note. A two-month process with a silent stretch in the middle is where most self-directed candidates assume rejection and stop following up. Someone chasing on your behalf is the difference between a stalled application and an offer.

She names Vishakha as her contact: “She shared leads, checked in on my interview progress, and made sure I stayed updated.”

Pros and Cons, Based on Hansika's Account

What worked:

• Access to partner companies during a tight job market
• A professionally rewritten CV that made use of her internships
• Persistent follow-up when the employer went quiet mid-process
• Job leads through LinkedIn
• An offer after a run of interviews that had produced none

What her account shows honestly:

• The role includes administrative tasks written into the contract alongside the analytics.
• The work is largely Excel, not the wider analytics stack.
• She wanted to be placed outside Mumbai and was not.
• The market was tight — her own framing, and only two companies interviewed her.
• The process took two months, including a period where the employer went silent.
• No salary is disclosed and no rating was asked for or given.

Data Analyst Interview Questions and Model Answers

What technical skills do you have, and how have you applied them?

Model answer: Excel to an advanced standard — consolidation, lookups, pivot tables and cleaning — plus the statistical grounding from an economics and behavioural data science background. Applied on internship work rather than only in coursework, which is where you learn that most of the job is getting messy inputs into a usable shape.

How do you consolidate raw data from multiple sources?

Model answer: Standardise the structure first — column names, data types, date formats — so the sources are actually comparable, then combine on a reliable key. The failure mode is joining on a field that looks unique and is not, so I validate row counts before and after and check for unexpected duplicates.

How do you handle confidential data?

Model answer: Treat access as the control, not the file — work only within approved systems, never move data to personal storage, and share outputs rather than underlying records. In a legal or financial context, the audit trail matters as much as the analysis, so document what was accessed and why.

Why does Excel still matter if you know Python?

Model answer: Because it is what the business already uses. Data arrives in it, stakeholders read it, and the first version of almost any analysis happens in it. Python scales the work later; Excel is what makes the first day useful.

Describe analysing data for a non-technical audience.

Model answer: Establish what decision the output supports before choosing how to present it. Lead with the finding, keep the visual simple, and hold the method in reserve for whoever asks. If the audience has to work out what the chart is arguing, the analysis has not finished.

Why do you want this role?

Model answer: Because it is analysis with real consequence attached — specialised data where accuracy is not optional. My background is economics and behavioural data science, so working with structured, sensitive datasets is what I have been trained for rather than a stretch.

Hansika's Advice for Non-Technical Candidates

• Master Excel first. Her words: “it's crucial at every stage of data analytics. Even if you're aiming to work with Python or machine learning, you'll always deal with Excel in the beginning.” Her own job proves the point.
• Talk to working professionals on LinkedIn. One-to-one conversations, not just following content.
• Use those conversations to test fit. Her reasoning is that they tell you what the role actually entails and whether it suits you — before you commit to it.
• Get your CV professionally rewritten. Hers was the thing that changed between interviews-without-offers and an offer.
• Keep following up when an employer goes quiet. Silence in a two-month process is not a rejection.

Full Podcast Transcript

The complete conversation, unedited.

Frequently Asked Questions

Is Jobaaj Learnings genuine, or is it fake?

This page documents one recorded case: Hansika, an MSc in Behavioural and Data Science who was getting interview calls but no offers, placed as a Data Analyst at DRRT after a four-round, two-month process. Employer, domain, rounds and coordinator are named on camera, and she volunteers that the role includes administrative duties. No salary is disclosed. See the wider review set on the reviews page.

Why do I get interview calls but no offers?

That was Hansika's exact problem. What changed for her was a professionally rewritten CV that made proper use of her internships, access to partner companies, and someone following up when an employer went quiet mid-process.

What does the DRRT data analyst role involve?

Uploading raw data, consolidating it and analysing it in Excel at a legal firm handling confidential shareholder data — plus administrative tasks specified in the contract.

How many interview rounds were there?

Four: an HR screening call, an in-person technical test and short interview at the Mumbai office, an HR round with the US team, and a final round with the US department head. About two months in total.

Which skill should a non-technical candidate learn first?

Excel, in Hansika's view — and her own job supports it. Her point is that even if you are aiming at Python or machine learning, the early work will be in Excel regardless.

How do you find out whether a role suits you before applying?

Her advice: reach out to professionals on LinkedIn and have one-to-one conversations. They tell you what the job actually involves and whether it is a good fit — which a job description will not.