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A year of experience as a Data Scientist

On June 3rd 2019, I joined ZS Associates as a Data Scientist after graduating from IIIT SriCity. It was my first job and was very happy to get placed as a Data Scientist through lateral hiring. If you haven’t read my Data Science journey, please read it here :)

After joining, I had some awesome moments that I never experienced since childhood.
  • I got a chance to stay in a 4 star or 5 star hotel multiple times.
  • I got a chance to travel by flight. I travelled to Pune, Delhi and Bangalore. I saw Vizag, Pune, Delhi and Bangalore airports in less than six months. I loved it.
  • A few office parties, outings during Diwali and New year celebrations.
Above are some of the moments that I can never forget in my life. My first job allowed me to experience these first time moments. Enjoying life is more important than anything. If you don’t enjoy your life, you cannot achieve anything big.

Okay, let’s go into the main topic in detail.

Me (inner voice during BTech): I know a bunch of algorithms and participated in a few hackathons. I got some experience in solving problems. I can model anything if I have data. I can start applying for jobs and help industries solve problems using Data Science.

After one year...

Me (inner voice after one year of experience): It’s not as simple as I thought during BTech. Solving real-world problems involves a lot of things. Domain knowledge plays an important role. Learning Python (pandas), Keras alone cannot solve all the problems. It’s all about solving problems with the help of technology and tools available.

I am not saying that I was wrong during BTech. The environment around us makes us think like that. It can be because of the limited information available with us or lack of guidance. But, I suggest students spend more time on learning modelling algorithms, improving mathematical skills, participating in hackathons etc. Because, these are more important skills to have to crack a data science interview. You can build your skills while working on real projects.

In my view, the below points are very important to be a successful Data Scientist:
  1. Domain knowledge: As a data scientist, we are extracting insights from the data. If we are not aware of what the data is about, how can we extract insights? So, data scientists should spend some time understanding the business problem.

  2. Continuous learning: Data Science is an ocean. It cannot be mastered in a few days. Frankly, no one can learn everything related to Data Science. Based on the problem, we should quickly explore new algorithms, tools, etc. Of course, there will be people around to help you if you are stuck at something.

  3. Enjoying your role: Sometimes, data science can be frustrating. You may not find enough resources on recent developments or you may face different challenges that were not solved before. In these situations, be patient and enjoy your work. Be curious to learn and explore new technologies.
One more point that I want to stress here. We are using Data Science to help and grow businesses. The domain in which we are applying Data Science can be different, but the main goal is the same i.e., using data to grow businesses. For example, Amazon uses customer data to improve their recommendation systems. This will help customers to buy more items from Amazon and in turn, helps them to grow their sales/business. In the above example, Amazon is using data science to grow their business.

In some cases, Data Science alone cannot impact customers/end users. To build a successful tool, many teams are involved starting from Software Engineers, Data Engineers, Dev Ops Engineers, etc. It takes effort from multiple teams to build a product. So, we should respect all roles. This is something that everyone should understand.

Coming to my learnings, I explored new algorithms/techniques and solved problems using PySpark, Dask, SQL, python libraries, etc. The list goes on based on the requirement. As a data scientist, learning shouldn’t stop. It’s really fun :)

As a daily routine, I do experiments, involve in brainstorming sessions, discuss insights, write emails, explore new algorithms, etc.

The above information is based on my experience and views. It may change based on team, company, etc. Please note that this article is only for educational purposes.

Thank you so much for reading my blog and supporting me. Stay tuned for my next article. If you want to receive email updates, don’t forget to subscribe to my blog.

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