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My Data Science Journey and Suggestions - Part 3

Written by Abhishek mamidi, on

If you haven't read the Part 1 and Part 2 of my Data Science journey, I recommend you to read it before you go through this article. Link to the Part 1 and Part 2.

In the sixth semester, I worked on multiple Deep Learning projects. Neural Artistic Style Transfer was one of my favourite projects I have worked on. I have used TensorFlow in this project and this was my fist Computer Vision project. I enjoyed doing it. I felt that I had a decent number of projects on my profile. So, I started applying to Data Science internships through LinkedIn. I requested my connections on LinkedIn to refer me in their companies. I received calls from a few companies. I gave interviews and ended up with two offers, one from a startup and another from a well established company. After doing research and reviews on glassdoor, I accepted the Data Science Summer Internship offer from Monsanto. It was a unique experience giving interviews from various companies.

I am fortunate to get an internship at a very good company which helped me to boost my career in the field of Data Science. My mentors helped me in both personal and technical development. This internship was a life changer for me. During my internship, I was exposed to half-day hackathons. Hackathons are really helpful to learn things in very less time. They encouraged me to participate in hackathons, write posts on LinkedIn. I followed their inputs and the results were amazing.

In the seventh semester, after the internship, I continued participating in Data Science hackathons on HackerEarth. I started sharing my knowledge and achievements through LinkedIn posts. The Data Science community on LinkedIn was very huge. I started Kaggle in the month of October 2018. I learnt a lot of visualization and preprocessing techniques in just three months. I became "Kernels Expert" after continuous effort. I successfully completed Statistics and Data Mining courses that were provided by the institution. These courses helped me to get an intuition of different machine learning algorithms deeper.

I have also worked on Time Series analysis on Maharashtra Rainfall data, which was a research project. We bought the rainfall data from the IMD website for this project. The real data science starts only when we work on real data. During this project, I read Time Series Analysis book, written by Box Jenkins. This was really a good book. If you have time, I suggest you read this. I have created multiple kernels on Kaggle on time-series data. If you are a beginner in time series analysis, do explore my kernels. I have used both traditional and deep learning methods to solve the problem.

By this time, I had a decent Data Science profile. So, I started applying to jobs through LinkedIn. I was looking for a Data Science job in MNC. I applied to 50+ companies and got a response from 5 companies. I gave interviews to all the companies. The interview process was completely different from company to company. But, there were at least 3 rounds. I was ended up with 3 Data Science Associate offers. For one of the company, the interview process had 6 rounds and I was able to crack all of them, but due to some reasons, they delayed the offer. In the end, I happily accepted the offer from ZS Associates for the role of Data Science Associate.

The struggle was real. We don’t get a response from every company that we apply to. We need a lot of patience and trust in ourselves. It took me two years to explore different domains of Data Science and struggle for six months to get a job offer. Now, I am proud of myself.

Final Suggestion:

The competition is very high. Sometimes, our resume may not reach to HR, due to the number of resumes they receive every day. So, we need to stand out of the crowd. I suggest everyone spend time on improving their skills and profile. Data Science is an ocean. We cannot master it in a few days. It will take time and consistency.

Hope, my journey will help you to make good decisions in your Data Science career. If you have any queries, comment in the comments section below. I would be more than happy to answer your queries.

Thank you 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. Keep learning and sharing!!

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GitHub: https://github.com/Abhishekmamidi123
LinkedIn: https://www.linkedin.com/in/abhishekmamidi/
Kaggle: https://www.kaggle.com/abhishekmamidi
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Comments

  1. yashSeptember 8, 2019 at 4:04 PM

    I read your all of the three posts, it taught me a lot. Thanks for writing. I want to get a job as a data analyst, i have started learning about data science from 7th semester, can I get a job at the end of my b.tech(computer science)?? Is it possible in 1 year , if yes, then how ??

    ReplyDelete
    Replies
    1. Abhishek mamidiSeptember 8, 2019 at 4:11 PM

      Thank you for reading all my articles. Yes, it is possible. I wrote an article on skills required to become a data scientist.

      Here is the link: https://www.abhishekmamidi.com/2019/07/skills-required-to-become-a-data-scientist.html

      Make sure that you re comfortable with all the skills that are mentioned in the blog. And then start applying to jobs. I highly suggest you participate in the Data Science hackathons.

      Delete
  2. This article will help youFebruary 5, 2020 at 5:42 PM

    I am glad to hear the news, that you managed to get a job in a company. Not everybody can have such a good opportunity. I wish you good luck.

    ReplyDelete
  3. UnknownMarch 12, 2020 at 9:00 PM

    Very inspiring journey, Thats great Abhishek.

    ReplyDelete
  4. UnknownApril 15, 2020 at 7:12 PM

    Hi Abhishek , Your journey is really inspiring.
    I too started my journey from deeplearning.ai course of coursera , as a part of job work I also happened to work on Arbitrary Neural style transfer .
    I am also new to this field and from ECE , do u suggest having a good knowledge on web development and software product development and related skills are very much necessary ?

    ReplyDelete

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