Meet Amber Jain from Accenture

At INSAID, we create accomplished and empowered Data Leaders. We groom our students to dominate the world of Data Science and Artificial Intelligence and reshape their future. We value what our students bring to the table. We share their vision and support them during their journey and ensure that they carve a niche for themselves.

We’re proud to have tutored exceptional students all across India. Today, one such exceptional student, Amber Jain stands in the spotlight.

Student Name: Amber Jain
Batch: CDF February 2019
Total years of experience: 3 years
Area of expertise: Application Development

Malvika: Hi Amber, can you walk me through your professional journey so far?

Amber: Currently I’m an Application Development Analyst with 3 years of experience in Accenture. I have experience in Python and machine learning Documentum. Along with that, I have worked with other engineering tools like eRoom and Hummingbird. I also have experience in introducing automation in all the tools for account creation. I am currently working on 17 applications; the main five being Documentum, Hummingbird, ITSM, ProjectWise and eRoom.

Malvika: Can you tell me what got you specifically interested in Data Science and Machine Learning?

Amber: Data Science is mainly concerned with playing around with numbers; something I’m really good at. With all the major turns happening in the industry, this looks a very promising field. I have a technical background and I was always very good in mathematics so I chose this field.

Malvika: Were there any initial challenges that you faced when you started your journey with data? And how did you overcome them?

Amber: I did struggle with learning Python. I had to practice Python programming rigorously to master it. I took up projects and gave a good number of hours to learn the language. Finally, I can say I’m comfortable with it.

Malvika: What do you think is the goal of Data Science?

Amber: The basic goal of Data Science starts with converting a business problem into a Data Science problem. That way you can uncover patterns that are being formed by data quietly in the background. So the end goal is to solve business problems and unleash their full potential using Data Science.

Malvika: Are there any current trends of Data Science that you are excited about?

Amber: E-commerce websites are redefining business using recommendation engines.
Suppose you were to buy a pen-drive online, recommendation systems would use clustering to suggest products like laptop bags, screen guards or keyboard guards. Sometimes these systems also gather information by asking about your purchase history like whether the shopkeeper/ vendor you contacted, provide home deliveries or whether the electronics store has other products to offer.

Malvika: Amber, are there any packages or libraries in Python that you find most useful?

Amber: I like Numpy and Pandas. Since I have experience working with Java I can draw a comparison here. In Java, if I had to get data from Excel to just simply in any other file, I’d have to write 20 lines of code but with Python, all those long lines of codes have been done away with. I really like how user-friendly Python is.

Malvika: At INSAID, students are encouraged to build high-quality Github profiles. Have you built a Github portfolio and how do you think this will help you?  

Amber: As of now I have an updated profile and one project to display on Github. In the near future, I see myself building a robust portfolio and communicating all my work with my peers, recruiters and seniors. It is an excellent repository but my use of it is mainly futuristic. 

Malvika: INSAID’s mission is to groom Data Leaders of tomorrow. What do you understand by a Data Leader? How do you think a Data Leader is different from a Data Scientist?

Amber: A Data Scientist solves the current problem at hand with research and statistics while a Data Leader is concerned with managing teams to reach their goals and solving business problems. A Data Leader is somebody who manages Data Scientists and monitors the workflow. 

Malvika: Amber, in the end, do you have any advice for a newbie in the Data Science space?

Amber: I consider myself as a newbie as well. While I can’t give a holistic piece of advice, I do want to emphasize the power of community and perseverance. The drive to see things to completion must come from within you but you can always seek support from your rightful community. Building a strong network and reaching out to your community from time to time is essential for both exposure and problem-solving.

Malvika: These are all the questions I have for you today. Thank you for sharing your time with us. Good luck for the future, Amber!
 

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