In this blog, we're sharing a real podcast conversation with Kavya, a learner from the Jobaaj Data and Business Analytics Program who successfully transitioned into a Marketing Analyst role at Deloitte. This is part of our Placed Candidates Podcast Series, where we bring you firsthand stories from students who transformed their careers with us.

Kavya comes from a marketing background, shifted into operations, and then pivoted into analytics with the help of the Jobaaj community. Let’s dive into her inspiring journey, her interview experience, the tools she uses at work, and her advice for aspiring analysts.

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Podcaster:
So today we have Kavya with us. She got placed as a Marketing Analyst in Deloitte and she's a part of the Jobaaj learning community. We’ll try to understand her background, skillset, daily work life, and the job role she got selected for. Kavya, welcome and thank you so much for joining. Can you start by telling our students about your educational background?

Kavya:
Yeah, sure. Thank you for having me here, Rakshit. Coming to my education background, I’ve done my MBA in marketing from Gayatri College in Visakhapatnam.

Podcaster:
Okay, and when did you complete that? This year itself?

Kavya:
No, I actually have experience prior to Deloitte. I worked in operations for about three years.

Podcaster:
Okay, so you had three years of operations experience, then you did your MBA, and then you joined Deloitte?

Kavya:
Not exactly. I did my MBA and then started working in operations. But I wasn’t very happy in that field. I wanted to move into data analytics. So I took a break, joined the Jobaaj program, and then applied for analyst roles.

Podcaster:
Got it. So you had a proper interview process for this marketing analyst role?

Kavya:
Yes.

Podcaster:
What kind of questions were asked, and how many rounds did you have?

Kavya:
The first round was with the manager — a mix of technical and managerial questions. They focused on Excel skills, data analysis basics like normalization, central tendency, and handling unclean data. The weekend classes at Jobaaj really helped me there.

Podcaster:
So the first round was technical and data-focused. What happened next?

Kavya:
The second round was an Excel assessment. They gave practical tasks and one hour to complete them on a virtual call. It wasn’t about building dashboards, but more about cleaning data, arithmetic formulas, and pivot tables.

Podcaster:
And how many rounds in total?

Kavya:
Five rounds in total. After the Excel test, there was a communication round, then a behavioral round with three managers, and finally, a conversation with the VP of the marketing team.

Podcaster:
That’s quite a process! So have you already joined Deloitte?

Kavya:
Yes, it’s been three months now.

Podcaster:
What’s your day-to-day role like? What tools do you use?

Kavya:
I work in the data reporting and automation team that supports Deloitte’s Australian marketing team. They request reports and dashboards, and we deliver them. We use Tableau for dashboards, Excel for smaller datasets, and VBA for automation tasks.

Podcaster:
VBA within Excel, right?

Kavya:
Yes, exactly.

Podcaster:
So for students who want to enter analytics, what core skills do you think they should learn?

Kavya:
Excel is the foundation. You should be strong in that first. Then, pick one dashboarding tool — Power BI or Tableau. Once you know one well, learning the other becomes easy. And Python is also becoming critical. In our firm, they even say Python is the new Excel.

Podcaster:
Many people get confused between roles like marketing analyst or HR analyst. But the tools and data analysis processes are quite similar, right?

Kavya:
Exactly. In marketing, we don’t handle transaction data like sales, but we work with client databases. The data types might change, but the process of analysis is more or less the same.

..............

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

 

General interview questions answered by Kavya during her selection process

Why did you switch from operations to analytics?

Sample Answer: During my time in operations, I realized that I enjoyed working with data more than anything else. I found data analysis both logical and impactful. I decided to take a break and focus on building analytics skills, which led me to transition into a data-focused role where I could contribute more strategically.

What is data normalization and why is it important?

Sample Answer: Data normalization is the process of organizing data to reduce redundancy and improve consistency. It involves breaking down large tables into smaller, related tables and linking them using keys. This helps ensure data integrity and makes the database easier to maintain and query.

How do you clean messy or unstructured data in Excel?

Sample Answer: I use Excel tools and functions like Remove Duplicates, TRIM, CLEAN, and filters to handle unclean data. For formatting and fixing errors, I also use IFERROR, PROPER, and manual spot checks. Consistency checks and using conditional formatting also help spot anomalies quickly.

What is central tendency, and how is it used in analytics?

Sample Answer: Central tendency refers to measures like mean, median, and mode that represent the center of a dataset. These metrics help summarize and understand the general trend in data. For example, calculating the average click-through rate helps evaluate the performance of marketing campaigns.

What Excel functions do you commonly use in reporting?

Sample Answer: I frequently use VLOOKUP, INDEX-MATCH, IF, SUMIFS, COUNTIFS, and logical operators. PivotTables are essential for summarizing data. I also use data validation and conditional formatting to ensure clean and readable reports.

What is VBA and how have you used it?

Sample Answer: VBA stands for Visual Basic for Applications. I’ve used it in Excel to automate routine tasks like report generation, formatting, and running macros for repetitive processes. It has helped save time and reduce human errors in reporting.

How do you build a dashboard for a marketing team?

Sample Answer: I begin by understanding what metrics the team needs, such as campaign performance, engagement rates, or ROI. Then, I clean and structure the data in Excel or a database. I use Tableau to create interactive dashboards that allow users to filter data and view insights visually and clearly.

Have you worked on real datasets before? What challenges did you face?

Sample Answer: Yes, I work with marketing and client data at Deloitte. One of the common challenges is dealing with missing or inconsistent data from multiple sources. I address this by cleaning the data thoroughly, maintaining documentation, and sometimes reaching out to data owners for clarification.