Meet Nitesh Srivastava from Oracle - INSAID Blog

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At INSAID, we create accomplished and empowered Data Leaders. We groom our students to dominate the world of Data Science and AI 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, Nitesh Srivastava stands in the spotlight.

Student Name: Nitesh Srivastava
Current Organization: Oracle
Batch: GCDAI – July 2019
Total years of experience: 14 years

Malvika: Hi Nitesh, before we begin, could you tell us more about your current work profile and your career trajectory so far? 

Nitesh: Currently I am working with Oracle as a Customer Success Manager for SaaS Applications.

It is actually comprised of a 70:30 ratio for managerial and technical work. As Oracle, we own the product. So, our main KPI is to make the customer journey with Oracle as smooth as possible. So that’s my main KPI here.

It includes stakeholder management, risk aversion and risk mitigation. So that’s my current role.

As far as my journey is concerned, I have an overall 14 years of experience with the Oracle product consulting. During this whole tenure, I worked with different verticals including BFSI, travel, education and health care.

And in the starting period, I was mainly about technical consulting, including Java, .Net, and other programming languages. We used to do configurations and customized issues integrations. So it’s overall mostly technical work in my 8-9 years of experience.

Afterwards, I moved to this Customer Success Manager role and from there, it’s just mainly more about customer advocacy that I am currently pursuing.

Malvika: What got you interested in Data Science & Machine Learning? 

Nitesh: As I said that my current role is 70:30 of management: technical. Personally, I felt like I should come back to my technical role again.

Firstly, this may be my personal preference and secondly, I am seeing a world moving towards digitalization, where everything is based on machine’s outputs. I feel like I can add value to a world like that.

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

Nitesh: Before this, I had never worked on Python earlier. Python is the first tool I learned and then for editors for Python, I use Jupyter and PyCharm.

So that’s very basic that I started with. I then migrated to learning Pandas, NumPy, SK Learn, and Matplotlib for visualization.

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

Nitesh: As I said I come from, IT-enabled-services industry, wherein it is used in different businesses and verticals to improve their businesses.

So, for me, the biggest example you can see is sentiment analysis, because, in our fields, customer satisfaction and customer feedback is the most important part. So Data Science or Machine Learning can be widely used in analyzing customer sentiment.

There are other aspects also like making the tool/service/product more interactive and more smart in a way that it will analyze the previous data from the customer and try to predict to improve sales, improve service, and many other aspects.

Chatbots are another example where Data Science is playing a key role in ITeS  services. 

Malvika: How has your journey with INSAID been so far? Do you have any comments on how the curriculum has been structured, the faculty and the support team?

Nitesh: I am bent more towards learning; learning from various channels.

It may be a tweet, it may be YouTube’s videos and of course, a lot of content is available on the internet but it’s very easy to be lost in that and you will never know what is happening,

What to study? How much to study? So, INSAID has definitely helped me in channelizing the knowledge answered questions like how to obtain more knowledge as the curriculum progressed, I came to know what to read and how much to read.

So that is something I really appreciate. It has given me a way how to go forward and what to read. INSAID has always encouraged me to be more hands-on with my projects because without that there will be no real progress.

Malvika: Have you attended any of the speaker sessions that we have at INSAID?

Nitesh: Definitely, these sessions were conducted by industry experts from various companies and those companies are deeply involved in this field of Machine Learning.

Even I have 14 years of experience in the Cloud. So my conversations about the cloud always add value to my customers. 

A few of them, also emphasized on focusing on theory because learning theory is most important in AI & ML because implementation requires a 1-2 liner code, where we just train the model and predict, but what is happening inside, what parameters we pass it’s a must to be known.

Malvika: Crafting a great Data Science resume is a critical part of getting shortlisted for Data Science roles. Tell us some ways in which you have improved your resume as part of Data Science Career Launchpad.

Nitesh: Resumes are like first interface with your employer so we can showcase our personal and professional capabilities in the resumes.

During this whole Launchpad session, the one focused on resume-building sessions was most useful because, after 14 years, I have a lot of things to write in the resume but the session was very clear that if you are 10+, then you should not just put everything into your resume.

I have filtered the content of my resume based on what my achievements or what my technical capabilities were, kept it not as detailed but yes, well-highlighted.

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?

Nitesh: GitHub is available widely, and it makes my life easy.

I can maintain my own source code because if I maintain everything on my laptop, it’s going to be at risk. So this is one aspect.

The second is sharing my work with my colleagues or with my co-students is very easy. If they ask for any help or any usable code that I can share with them. So, I give them the link of my work done in GitHub and then they can refer there.

Third point, mentioning your GitHub profile in the resume gives you an edge because you need not worry that how your employer will see your work, what you have done and what you haven’t and how you have done and many other aspects.

When the recruiter is looking at your GitHub profile, they will go through many pointers like how neatly did you document it, and how have you presented all these things.

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

Nitesh: What happens is Data Leaders come from among Data Scientists only.

So, to be a leader, you have to pass through certain steps because if you don’t, if you have never faced those challenges, or that kind of experience, you won’t be able to guide the people.

So the first quality is to guide people to show them the right thing. So definitely a Data Leader has to go through a Data Scientist’s role earlier. In one day, nobody can stand up and become a Data Leader.

A Data Leader’s main job is to obviously lead and motivate others as much as know how to exploit the data, how to get insights from the data.

Malvika: Who is your favorite faculty at INSAID and what did you learn from him the most? 

Nitesh: As far as teachers are concerned, my opinion is any teacher is good actually.

Some faculty have a different way of teaching that aligns with their students mentality, and that’s how they become the favorites.

At INSAID, I have interacted with various faculty starting from Manav. He has impeccable skills of marketing and storytelling. Storytelling is something that every Data Scientist should be able to do.

Secondly, Suchit; he has a thorough knowledge of his field, and he involves students in the class.

Currently, we are going through Deepesh’s class and his unique way of teaching on the paper and pen is making him a widely loved faculty across INSAID. So those are my inputs on INSAID’s faculty.

Malvika: Thank you for your time, Nitesh. All the best for your future!

Author

Content Writer @ INSAID. A machine learning buff who loves to read, write and explain everything AI!

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