This blog shares the inspiring journey of Karthik, a commerce graduate who transitioned into the data analytics field with the help of Jobaaj Group’s placement support. Originally working as a Data Analyst at IIFL Bank, Karthik was successfully placed at FedEx as a Data Analytics Associate. In this podcast conversation, Karthik talks with Harshit from the Jobaaj Digital Marketing Team, reflecting on his educational background, career journey, and experience with the Jobaaj team.

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Podcaster:
Okay, so Karthik, my name is Harshit, and I head the digital marketing team at Jobaaj. I'm extremely grateful that you have joined this call. Thank you so much for connecting. Karthik, can you give me a little introduction about your educational background—where you studied and what degree you’ve completed?

Karthik:
Yeah, sure. I completed my Bachelor’s in Commerce from Sapient College, which is under the University of Mexico. That’s my highest degree. Apart from that, I’ve done certification courses in Data Analytics and Machine Learning through various platforms. That was the major push in my education after college.

Podcaster:
Okay. And which company were you working in before this placement?

Karthik:
I was working at IIFL, a microfinance institution, as a Data Analyst.

Podcaster:
And what was your job profile like there?

Karthik:
I was mainly working with mid-sized datasets—around 40 to 50 lakh records. I used tools like Python and SQL.

Podcaster:
Great! So where have you been placed now, and what does your role look like?

Karthik:
Right now, I’ve been placed at FedEx as a Data Analytics Associate. I’ll be joining their Pricing Team where I’ll be working with data related to pricing strategy. The job will involve a lot of data cleaning, handling, and technical tools.

Podcaster:
That sounds like a great opportunity. You must be excited! When do you join?

Karthik:
Yes, I’m totally excited. They’ve asked me to join by Christmas.

Podcaster:
Will it be hybrid or work-from-office?

Karthik:
I haven’t asked that. Honestly, I don’t mind either way—I’m just excited to start.

Podcaster:
So the FedEx office is in Bangalore, right?

Karthik:
Yes, exactly.

Podcaster:
Let’s talk a bit about how Jobaaj helped you. Could you share how the process went from your end?

Karthik:
Sure. I had initially applied through Naukri, and honestly, I had no idea whether it would work out. I applied just because it was a Data Analyst role. When I got a call from your team, I was unsure if my profile would fit. But I was guided properly, and eventually I got an interview opportunity.

Karthik (continued):
The Jobaaj team helped me through every step—from scheduling the interview to follow-ups. They kept me informed, shared updates, and supported me until I received the offer letter.

Podcaster:
Who was your point of contact from our side? And how was the communication overall?

Karthik:
It was someone named Kashish. She was really helpful. I had missed the first call, but when I called back later, she explained everything clearly and without hesitation. She guided me well.

Podcaster:
That’s great to hear. And how was your interview experience—smooth or any issues?

Karthik:
It was all a bit sudden. I wasn’t sure the interview would actually happen because I thought my profile might not match. But things fell into place quickly. I came back, gave the interview, and it all worked out!

Podcaster:
Wonderful. It really looks like you’re excited for this new journey—and we’re excited for you too. Before we end, let me share a bit about Jobaaj Group. Do you know what we do?

Karthik:
No, not really.

Podcaster:
So, Jobaaj is a group of companies—Jobaaj, Jobaaj Learnings, and Jobaaj Café. The main arm is Jobaaj Learnings. We train students after graduation in trending fields like Data Analytics, Management Consulting, Product Management, Financial Modeling, and more. After 3–4 months of hands-on live training and projects, we also offer guaranteed placement support.

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Don’t miss the full conversation—watch the podcast now and get inspired by Karthik’s journey!

 

General interview questions answered by Karthik during her selection process

What tools and technologies are you most comfortable with?

Sample Answer: I’m most comfortable working with Python and SQL for data manipulation and analysis. I also have experience using Excel for quick data tasks and dashboards, and I’ve recently started exploring Tableau for data visualization. For Python, I primarily work with pandas, NumPy, and matplotlib.

Describe a data project or problem you solved at IIFL.

Sample Answer: At IIFL, I worked on a loan default risk analysis project. I cleaned and processed a dataset of over 40 lakh rows, using SQL for extraction and Python for analysis. We were able to identify key borrower behaviors that indicated high risk, and this helped the credit team refine their approval process, reducing bad loans by about 8%.

How do you handle missing or inconsistent data?

Sample Answer: First, I analyze the pattern of missing data—is it random or systematic? Then based on the type of data and business context, I either impute values using mean/median/mode or drop the records if they're minimal. For categorical variables, I use placeholders like “Unknown.” Consistency is achieved using standardization techniques like date formatting, case conversion, and removing duplicates.

How do you ensure the accuracy and quality of your data analysis?

Sample Answer: I follow a structured process—starting with data validation, using summary statistics, data profiling, and checking for outliers or logical inconsistencies. I cross-check outputs with multiple tools (e.g., comparing SQL and Python results) and ensure business logic aligns with the outcomes. Peer review and proper documentation also help ensure quality.

Tell us about a time you worked under pressure to meet a deadline.

Sample Answer: During a reporting cycle at IIFL, I had to clean and analyze a large dataset overnight due to a last-minute management requirement. I prioritized data cleaning scripts, parallelized tasks using Python, and completed a basic but accurate report within the given timeframe. My proactive communication with the team also helped us stay on track.

How do you communicate complex data insights to non-technical stakeholders?

Sample Answer: I focus on storytelling with data—using visuals like bar charts, trend lines, and pie charts with tools like Excel or Tableau. I avoid jargon and relate insights to business outcomes. For example, instead of saying "correlation coefficient," I might say "customers who delay their payments twice are 3x more likely to default."

How do you prioritize tasks when you’re managing multiple projects?

Sample Answer: I use a combination of the Eisenhower Matrix and deadline-based prioritization. Urgent-impactful tasks go first. I also break down big projects into smaller milestones and allocate time blocks. Tools like Trello or just a structured Excel to-do list help me manage time efficiently.

You come from a commerce background. How did you manage the technical learning curve?

Sample Answer: It was challenging initially, but I treated it like a full-time commitment. I followed structured online courses with projects and spent hours practicing Python and SQL daily. I also joined discussion forums and worked on real datasets to get comfortable with technical problem-solving. My commerce background gives me a business mindset, which complements my technical skills.