Meet Debapriya Dey Bandyopadhyay From RELX Group

While working with massive data sets, data mining and sorting, Debapriya Dey Bandyopadhyay realized the significance of data science applications. So, to upskill herself in data science and pave a better career path, she enrolled for the Global Certificate in Data Science (GCD) program at INSAID

In this interview, let’s take a look at what interests her in Data Science the most and how her learning experience has been at INSAID.  

Question 1: Which program & batch are you part of at INSAID & tell us more about your current work profile?

Debapriya: I am part of the Global Certificate in Data Science (GCD) program, August 2020 batch. In my current company, Elsevier, Relx Group, I am working as a Logistics Coordinator. I look after the outward and inward transactions from our eight warehouses PAN India, coordinate for timely dispatch of orders and delivery. I am also responsible for publishing detailed reports about the logistics distribution of all orders to internal stakeholders. I work closely with the warehouses to update all Oracle records and report in case of any kind of non-compliance.

Question 2: Walk us through your career journey & what got you interested in Data Science & Machine Learning?

Debapriya: I started my career at Su-Kam Power Systems as a management trainee and was appointed in the International Business department. Gradually I was assigned few territories to look after the business development in those areas. At the same time, I got an opportunity to learn about logistics operations. 

After four years, I joined Indo Asian, the Legrand Group in the Logistics division of International Business. I was responsible for arranging overall International logistics and commercial documentation, registering and keeping a record of Export benefits. 

After that, I joined TUF Metallurgical as Export Manager to handle the Asia Pacific Region’s tender business. Thereafter I joined Eastman Auto & Power after two years to look after logistics Operations, Export, Incentive management, MIS generation, Supervision of the Documentation team. 

There I handled a group of 4 and gained success in realizing Drawback and MEIS export incentives. Also I got an opportunity to learn liaising with Banks for negotiation of Export Bills and Procedures. In 2016 I took a sabbatical for three years to look after my new-born, and after that, in 2019, I joined Elsevier, The RELX Group, as Logistics Coordinator.

I deal with massive data sets in my current profile and perform data mining and sorting. Also, I use advanced excel to publish sophisticated reports to management. This was when I realized I need to get into Data Science and learn about the diverse available data science applications, which can take me to a higher level in my career and add value to my work profile.

Question 3: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at INSAID so far?

Debapriya: I have done my Bachelor’s degree in Statistics, and this program has helped me brush up on all the essential topics in Statistics that are used in Machine Learning. Also, I got an opportunity to learn Python, Numpy, and Pandas and their application. I also got to know about data visualization techniques and other data science applications.

Question 4: What are some initial challenges when you got started on your Data Science journey, and how did you overcome them?

Debapriya: I faced challenges in grasping Python, Numpy, and Pandas methods, and I am trying to get better at all these methods through practice. This is important to strengthen my basics so that when I apply for assignments in this field, I can be confident enough to meet organization goals and expectations.

Question 5: Who is your favorite faculty at INSAID, and what did you learn from him the Most?

Debapriya: In INSAID, our mentor, Suchit Majumdar, has given us basic knowledge about Statistics topics and Python through well-demonstrated presentations. This has helped me understand Python from a grass-root level. Also, the sessions with our professor, Sai, were very informative and well explained. I am thankful to both of them.

Question 6: What is the goal of Data Science?

Debapriya: The main goals of data science and data science applications include collecting, processing, exploring and visualizing data. It also involves analyzing and then applying Machine Learning techniques to Data Planning and making decisions based on the acquired insight about data.

Question 7: What are the current trends in Data Science that you are most excited about?

Debapriya: A few of the data science applications’ trends that interest me are Graphic Analytics, Deep Learning, Data Warehousing and Data Management Platforms. I am also interested in the use of Data Science for organizational management.

Graph Analytics acts as a flexible yet powerful tool that analyzes complicated data points and relationships using graphs. Deep Learning enables largely unsupervised learning against unstructured data in a bid to return hidden signals. Deep understanding will free up the time of in-demand data scientists to connect insights to action.

At present, many business teams also preferring their team members use data science applications and analytics tools to analyze data. There is a movement where data science skills are built within business teams. Business teams are learning how to manage data science projects, expectations, and timelines and how skills and team management are different from those in traditional software development teams.

Apart from that, the past few years have also seen the emergence of many warehousing services and platforms. These can be used by data engineering teams to kickstart their data warehousing processes. 

This was a conversation with one of our GCD students – Debapriya Dey Bandyopadhyay.

Discover more such interesting student interviews at INSAID Spotlight.

Total
0
Shares
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