In this blog, we bring you an inspiring podcast featuring Hansika, a recent graduate from our Data and Business Analytics program, who secured a placement as a Data Analyst at DRRT. Hansika shares her journey of how she transitioned into the field of data analytics, the role she plays at her new job, and the support she received from Jobaaj in securing her placement. If you're considering a career in data analytics or looking for guidance on how to navigate the job market, this podcast provides valuable insights.

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Podcaster:
Hi, how are you, Hansika? And congratulations on being placed as a data analyst. So, how are you?

Hansika:
I'm good. Yeah.

Podcaster:
Can you please give me a brief about the company that you've been placed in and what kind of company it is and what kind of work does it do?

Hansika:
It's a legal firm that handles confidential data related to shareholders and their dealings. So, that's what the company is about. The data analyst role mainly revolves around handling and analyzing data in Excel.

Podcaster:
What is the name of the company?

Hansika:
It's DRRT.

Podcaster:
Okay, great! And can you give a brief about what roles and responsibilities you have in your data analyst role?

Hansika:
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.

Podcaster:
Great! And can you tell me a bit about yourself? What is your educational background, and do you have any work experience or internships?

Hansika:
Sure. I did my bachelor's in Economics and then my MSc in Behavioral and Data Science. After my MSc, I took a break and did internships at NSC India and Home Finance. 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, who helped me secure a role at DRRT.

Podcaster:
Why did you choose data analytics? What inspired you to pursue this field?

Hansika:
It was a natural progression for me. Economics involved a lot of statistics, and when I did my MSc, it had a strong focus on data science and analytics. I developed an interest in it and decided to pursue a career in data analytics.

Podcaster:
What advice would you give to people from non-tech backgrounds who want to get into data analytics?

Hansika:
My advice is to start by mastering Excel – 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. I’d also suggest reaching out to professionals on LinkedIn and having one-on-one conversations. These interactions will give you a much better understanding of what the role entails and whether it’s a good fit for you.

Podcaster:
Thank you for the helpful suggestions. Now, could you tell us about your interview process? How many rounds were there?

Hansika:
The first round was an HR screening call. The second round required me to visit their Mumbai office for a technical test and a small interview. The third round was an HR round with the US team, and the fourth round was with the department head of the US team. Overall, there were four rounds, and the entire process took about two months, with the interview phase lasting about 2-3 weeks.

Podcaster:
How many interviews have you given since being with Jobaaj?

Hansika:
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.

Podcaster:
Where are you from?

Hansika:
I’m from Mumbai, India.

Podcaster:
That’s great! It must be very convenient for you to be placed in Mumbai, right?

Hansika:
Yes, it’s convenient, but I did want to be placed outside the city.

Podcaster:
How did the placement team at Jobaaj help you in securing this position and during the interview process?

Hansika:
Jobaaj was really helpful in reaching out to their partner companies, especially when the job market was tight. They also helped me craft my CV, incorporating my previous internship experiences, and ensured it was done professionally. Even when DRRT took time to respond, the Jobaaj team helped me stay in touch with them. They also provided job leads through LinkedIn, which simplified the job search for me.

Podcaster:
Who were you connected with from the Jobaaj placement team?

Hansika:
I was connected with Vishakha.

Podcaster:
Was Vishakha helpful in supporting you during the placement process?

Hansika:
Yes, Vishakha was great! She shared leads, checked in on my interview progress, and made sure I stayed updated. Overall, it was a smooth process.

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

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

 

General interview questions answered by Hansika during her selection process

What technical skills do you have in data analytics, and how have you applied them in your work?

Sample Answer: I have strong skills in Excel, including functions like VLOOKUP, PivotTables, and data visualization tools. During my internships and current role, I’ve used these tools to analyze large datasets, consolidate information, and generate reports. I’ve also worked on basic data cleaning and manipulation techniques to prepare datasets for analysis.

Can you describe the process you follow when given raw data for analysis?

Sample Answer: My first step is to clean and preprocess the data. This involves handling missing values, removing duplicates, and standardizing the format. After that, I analyze the data by performing exploratory data analysis (EDA) to identify trends and outliers. I then create reports or dashboards, depending on the required deliverables, using tools like Excel or other BI platforms.

Can you explain what a PivotTable is and how you’ve used it in your analysis?

Sample Answer: A PivotTable is a tool in Excel that allows you to summarize and analyze large amounts of data by grouping and aggregating the data in various ways. I’ve used PivotTables to quickly extract key insights, such as summarizing sales data by region or analyzing customer demographics. It’s an effective way to break down complex data into more digestible formats for reporting.

Can you describe a technical challenge you faced during your internship, and how did you solve it?

Sample Answer: During my internship at NSC India, I was tasked with cleaning a dataset with multiple missing values and inconsistencies. The challenge was to fill in the gaps without introducing bias. I used a combination of techniques, such as mean imputation and forward-fill for time-series data. I also collaborated with my team to ensure the solution was aligned with best practices and didn’t compromise the analysis quality.

How would you merge two datasets in Python using Pandas?

Sample Answer: In Python, I can use the merge() function from the Pandas library to combine two datasets based on a common column. For example:

import pandas as pd
df1 = pd.read_csv('data1.csv')
df2 = pd.read_csv('data2.csv')
merged_df = pd.merge(df1, df2, on='common_column', how='inner')

How would you perform data aggregation in SQL to calculate the average salary for each department from the employees table?

Sample Answer: To calculate the average salary for each department in the employees table, I would use the GROUP BY clause in SQL:

SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id;