Meet Manish Chandak from Hexagon

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, Manish Chandak stands in the spotlight.

Student Name:  Manish Chandak
Batch: GCD – November 2018
Total years of experience: 10 years 11 months
Area of expertise: software development for CAD CAM offshore industries

Malvika: Hi Manish, let’s begin with knowing more about your professional journey so far.

Manish: Yes sure. I’ve done my graduation in mechanical engineering, then I moved to a CAD-CAM engineering-based company called Intergraph, now Hexagon. Here I’m involved in software development in terms of content customization for the CAD-CAM offshore industries where I get to develop some computational geometries and topology symbols. So I’ve been supporting that from last year.

Along with that I’ve been managing a team and ensuring that whenever customers have any issues, I can service their request for them.

Malvika: Can you tell me what got you interested in data science and machine learning?

Manish: Yeah, what got me interested is that data science has immense potential to be a tool in this offshore field of engineering to start securing better solutions for the customers. You can use data science as a tool to automate a lot of stuff.
I also wanted to see what can we do in the field of process time management. We can leverage data science and machine learning to optimize this field and answer questions like what, when are where can we offer solutions?

Malvika: Manish, can you tell me the goal of data science?

Manish: The goal, simply put, would be to extract some meaningful solution from a business problem. If you use data engineering or data analytics, that would augment your analysis further but at the end of the day, if you’re able to pull out a solution, given the data then that should be the goal.

Malvika: Manish, are there any current trends in data science that you’re excited about?

Manish: So Malvika the trends that I’m following are more generic and not limited to specific industries, but since I was talking about offshore engineering, which is my current IT role too, I’d say I’m excited about all the automation we can bring into the manufacturing sector.  

I think there is a lot of potential with random substitution and random forest in this regard. We can run these algorithms across different products that we’ve been using. There’s a lot of automation coming our way and a lot of decisions will be made, I think that’s when classification algorithms will come more into play.

But other than that, there are some exciting applications happening all over like speech recognition and image recognition. I see monumental changes molded by these applications in the future.

Malvika: That’s interesting! Are there any data science or artificial intelligence influencers that you’re following?

Manish: There are so many influencers online that one can follow. Let me talk about two people who I relate the most with. First, there’s Mansa who I had the opportunity to interview during my professional journey and then there’s a previous colleague of mine who really got me going into the data science space.

Again, there are two aspects of them. One they’ve grown from the same field as me. They belong from the same community so it becomes easier for me to relate to their experiences. 

The second part is that they forced me to think about all the limitations in automation. Since automation is a big bet of tomorrow, we need to think what’s limiting us today.

The second idea is what I learned from Mansa. We are supposed to offer business solutions, bigger and better solutions but what we fail to understand is we have to be more perceptive about it. All the stakeholders in the world we are catering to, are in need of these solutions but they’re not aware of it. Essentially, we need to come out of our comfort zones, as data scientists, to be able to provide these much-needed solutions, that our audience isn’t even consciously thinking about.

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

Manish: Okay, I’ll keep this brief. Data scientist is someone who is getting his hands dirty with writing and developing algorithms while Data Leader is someone looking at the bigger picture and having a higher level of understanding. It’s the same as a manager and technical professional analogy. A data scientist is your technical guy while a data leader has managerial accountabilities. 

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?

Manish: Sure, I should really appreciate INSAID for this. Even though I’ve been in this field for some time this is the first time I heard about GitHub and explored it. I feel it really brings you close to technology, no matter what you use it for. As a professional, GitHub is highly important, you can reflect yourself completely no matter what industry you belong to. 

Malvika: Manish, my last question to you would be if you have any advice for a newbie starting out a career in data science? 

Manish:  Yeah, challenges can be several depending on your situation. If you are a working professional, you need to buckle up with the course, because you already have other commitments eating up your time. The most important thing is you need to practice and take out time for that.

As a fresher you need to understand there are a lot of data-sets out there, explore a little, you need to start practicing and assessing yourself.

Find problems to solve and work on. Finding a problem is again a big challenge, finding the problem statement, understanding the objective and then looking for solutions using data science as a tool. 

Malvika: Thank you for your time, Manish. On behalf of our team at INSAID, I wish you all the best for your future!

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