In our newest Success Stories blog post, we showcase Amber Jain, who is a Senior Data Analyst Engineer at Amazatic. Join us as he narrates his journey, from initially working in a startup, then joining Accredian’s Global Certificate in Data Science to stepping into the Data Science industry.
Discover more about Amber’s career transition and the impactful strategies he employs in shaping product offerings.
Q1. Tell us about your current role and background.
In my current role as a data engineer and data analyst, I play a crucial part in the organization’s data pipeline. I specialize in collecting and gathering raw data, a process that involves meticulous attention to detail.
What makes my work truly impactful is the transformation of this raw data into valuable, structured insights. These insights, in turn, empower our sellers, enabling them to make informed decisions and drive business growth.
It’s a dynamic role that keeps me at the forefront of data-driven innovation, and I take pride in contributing to the success of our team and the overall objectives of the organization
Q2. What challenges did you face while exploring a Data Science role?
So, one of the main challenges I faced was the need to effectively showcase the impact of my work as a data analyst and engineer within our current organization. In the support projects, I demonstrated my analytical skills by conducting thorough analysis on service requests and implementing automations.
I also applied data science algorithms and conducted data analysis to provide tangible evidence of my prior experiences in the field. This experience has fueled my interest in the data stream and further motivated me to excel in this dynamic field.
Moreover, I successfully tackled the challenge of illustrating the outcomes of my data engineering and analytics projects. This involved presenting tangible results that highlighted the value I brought to the organization.
In support projects, I not only showcased my data skills but also implemented innovative solutions, contributing significantly to the efficiency of our operations. These experiences have reinforced my commitment to delivering impactful results through my role as a data professional
Q3. How has Data Science helped you in your new role?
The Capstone project in the program really helped me a lot. I applied what I learned to a dataset, showcasing the same in my interview. I highlighted my achievements and shared my learning experiences during this project.
The courses and the Capstone project at Accredian provided valuable practice papers and questions, enhancing my skills.
Q4. What was the interview experience at your current company?
I progressed through three rounds of interviews. They went like:
1. SQL Round:
The first round involves questions related to SQL since, for every data engineer, SQL is the most basic and crucial language. I successfully solved the SQL questions.
2. Python Round:
After the SQL round, they inquired about Python, testing my knowledge in this language.
3. Machine Learning Algorithm Round:
In the third round, they delved into machine learning algorithms. I specifically discussed a machine learning algorithm and elaborated on its application and output.
4. Generic HR Round:
The fourth and final round was a generic HR round, focusing on more general aspects.
So, the interview process comprised three technical rounds (SQL, Python, and Machine Learning Algorithm) and one Generic HR round. SQL and Python skills were deemed most important for the position.
Q5. Why Accredian? How did it help you?
The course was very specific to data science and data analysts. Whether you want to transition to the data stream, these courses provide all the basic concepts, including statistics, probability, and Python.
The capstone project is also crucial, allowing you to use all the skills required for a data engineer/data analyst role or even a data science role. But for me, the main highlight is the capstone project.
And the best thing about Accredian is that whenever I have a question, I just drop an email, and within 24 to 48 hours, I get a response. Practicing or whenever I’m stuck, I take help from the faculty. The constant support certainly makes Accredian stand out from the rest.
Q6. What advice would you give to Data Science beginners?
For individuals venturing into the realms of data science, data analysis, or data engineering, a strategic approach is paramount.
Clarify your career destination early on: if aiming for a data engineer or data analyst role, comprehensive proficiency in SQL and Python is vital. For those eyeing data science, prioritize Python and delve into machine learning algorithms, focusing on your strengths.
Precision matters, therefore highlight specific machine learning proficiencies rather than an exhaustive list. Anticipate interview inquiries on your applied algorithms, both in past roles and capstone projects.
Freshers should prioritize SQL, engage in online projects, and exhibit their work on platforms like GitHub. Simultaneously, master Python, recognizing its foundational significance alongside SQL.
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