How BrijNandan transition from a Mechanical Engineer to Data Analyst Role


Meet BrijNandan Tripathi, the versatile and dynamic Data Analyst at EXL, whose journey from Mechanical Engineer to Data Analyst is nothing short of inspiring.

Get ready to be inspired and enlightened as we unravel the remarkable tale of BrijNandan Tripathi’s incredible transformation, proving that with the right mindset and dedication, anything is possible in the world of data and analytics.

Q1: Tell us about your current role & background.

Hello, everyone! I’m BrijNandan Tripathi, and I’m currently employed as a Data Analyst at EXL. I’ve been with EXL for approximately 1.5 years now. Prior to this role, I worked as a mechanical engineer with Total Oil, but I discovered a strong passion for data, which led me to make the switch to the field of data science.

Q2: What challenges did you face while switching to Data Science?

One of the initial challenges I encountered during my transition was a common issue many of us face: a lack of confidence. Whether it’s because we don’t come from a coding background or we question if this new field is our true calling, these doubts often creep in.

The self-talk often begins with skepticism. However, as you begin to collaborate with a team and immerse yourself in coding, you start to realize that it’s not as formidable as you initially believed.

With time, continuous practice, and a commitment to learning, you find that you can indeed excel in this field. As you work with data and delve into new concepts, your confidence grows, and the challenges that once seemed insurmountable become manageable and even enjoyable.

Remember, every expert was once a beginner, and your journey into the world of data science is no exception.

Q3: How has Data Science helped you in your new role?

My journey into the world of data science commenced during my tenure at Total Oil, where I served as a Research Scientist. My primary responsibility involved the rigorous testing of various oil samples, analyzing their distinct properties, and assessing the effectiveness of specific additives.

Throughout this experience, I came to appreciate the significance of precise calculations in determining the optimal percentage of these additives, leading to the best possible solutions.

It was during this time that I began integrating data science methodologies into my work. Starting with Excel, I gradually expanded my skills to include Python, and I also delved into utilizing the Power BI tool for data presentations. This marked the initial phase of my foray into the realm of data science.

Upon transitioning to EXL, I embarked on my first project within the banking domain. Currently, I am an integral part of the Fraud and Analytics Team, leveraging data insights to curate comprehensive dashboards. These dashboards serve as powerful tools for senior management, facilitating easy access to the precise information they require.

My journey in data science continues to evolve, and I remain dedicated to enhancing my skills and contributing meaningfully to the field.

Q4: What was the interview like at your current company?

Regarding the interview process, my journey began when I was contacted by a third-party recruiter. Initially, the focus was on understanding my requirements, especially since I was transitioning to a new domain. The first interview was conducted by the third-party, primarily to gauge my compatibility with the role and assess my potential to deliver in this new area.

After successfully passing through the initial screening, I moved on to the company-specific interviews at EXL. One of the standout aspects of the EXL interview process was the warmth and friendliness of the interviewers. It set the stage for a positive experience.

The interview rounds at EXL were as follows:

Stage #1-Technical Expertise: This round delved into my technical knowledge, particularly in Python. It was an opportunity to showcase my expertise in this key programming language. Additionally, the round included questions related to SQL, further testing my data manipulation skills.

Stage #2-Managerial Knowledge: Following the technical assessment, I advanced to the managerial round. Here, the focus shifted to my problem-solving abilities and my capacity to handle situational and procedural challenges. Many of the questions were centered around fraud analytics, which aligned perfectly with the role I was pursuing.

Stage #3-HR Round: The final leg of the interview process was the HR round. Its primary purpose was to evaluate how well I would fit within the company’s culture and ethics. It also touched upon my adaptability to a new market environment and similar considerations.

In total, the interview process consisted of 3-4 rounds. It was a comprehensive and engaging experience that allowed me to showcase my skills, knowledge, and enthusiasm for the role. The friendly demeanor of the EXL team made the process all the more pleasant.

Q5: Why ACCREDIAN? How did it help you?

Speaking about how Accredian contributed to my journey is an interesting story. To be honest, I wasn’t actively seeking a Data Science institute. It was on the 15th of August, a date etched in my memory as my first day there, that I stumbled upon a Facebook ad.

The ad suggested that if I wished to embark on a journey into the data science field, whether I had a coding background or not, I should consider Accredian. Intrigued, I decided to attend a one-hour introductory class, where they explained how this journey could benefit me and help me achieve my dreams in data science.

My first class, led by Suchit, was nothing short of wonderful. It set the tone for a series of excellent sessions by various instructors. Initially, I was told that the program was designed for six months, but due to unforeseen circumstances, particularly the impact of COVID, it extended to a year. This extension left me feeling somewhat skeptical about my decision.

However, what truly set Accredian apart was the unwavering support and guidance provided by the teachers and the entire staff. They fostered a welcoming, familial environment where I felt comfortable bringing my doubts and questions to them at any time.

This aspect made me feel less like I was attending a formal institution and more like I was engaging in discussions with a group of friends. The quality of education and the caliber of teachers at Accredian were truly commendable.

In summary, Accredian played a pivotal role in my data science journey, and it turned out to be an unexpected but extremely rewarding decision.

Q6: What advice would you give to Data Science Beginners?

One common piece of advice that resonated with me is the importance of patience. It’s a universal truth that everything, whether positive or negative, takes time to manifest its end result. What truly matters is that you give your best effort, putting forth 100%. In this journey, the concept of patience became especially relevant.

As you’ve probably heard, the course I initially signed up for was slated for six months but ended up stretching to a year due to unforeseen circumstances, like the impact of COVID.

Faced with this situation, I had a choice: I could either panic or take it as an opportunity to enhance my skills. I chose the latter, seeing the extra time as a valuable chance to practice and refine my knowledge.

The key lesson here is not to lose hope, especially when you’re just starting out. It’s natural to face challenges and setbacks initially. However, remember that these hurdles are a part of the learning process. Persistence is the key. Keep practicing until you gain confidence in your abilities.

While perfection may be elusive, the goal is to reach a point where you can approach any question with confidence. In the early stages, even if you face failures, remember this advice: never lose hope in yourself.

Keep pushing forward, keep practicing, and with time and dedication, you’ll find yourself in a better place.

We hope you found this success story interesting. If you have any Data Science questions, please fill out this form and we will get back to you.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Related Posts