Welcome to my profile
As a Senior Data Scientist and a Mentor, I help data enthusiasts break into and grow in the world of data science. I share learnings, my approach, and everything about my journey to become a successful data scientist, hoping to inspire you the achieve the same.
Besides, I’m embarking on a personal development journey. Who doesn’t want to become their better self? You can reach out to me on LinkedIn and join my private list of email friends to keep in touch and never miss an update.
My most-read articles:
I made a mistake. I’m going to fix it.
You probably already know me as a senior data scientist and a mentor. I have been sharing learning and experiences from my data science journey. The mistake? I started sharing only when I was 3 years into it.
You don’t see the mistakes I made. You never saw the hours I put in. You see a finished product: a senior data scientist. Wouldn’t it have been better if you saw it from the beginning?
But, in my defence, I was scared. What if people don’t find my learnings worth it? What…
Having worked in an AI startup, I was exposed to scoping and architecting AI projects much earlier in my career. I’m now a Senior Data Scientist and have worked on numerous AI projects in the past three years.
Even now, I feel every new project I work on has its learning curve. In the past, as a team, we’ve made many costly mistakes. Mistakes that cost us time, money, and energy. We learnt our lessons. These are lessons you can’t find in any degree program or online courses. You need to be there in the industry to face them.
Imagine waking up relaxed, full of energy, and smiling every day. I don’t know about you, but I had always thought these were only part of dramatic scenes in movies until I experienced it for myself.
It’s freaking real.
You can wake up smiling every single day. You will start looking forward to each day. The moment you experience it, trust me, there’s no going back.
In the past, I’ve never looked forward to my mornings. I’d have six alarms snooze before I’d finally wake up just in time to leave for work. If it were a weekend, I would…
My school teacher did something that stuck with me over the years.
After every class, she would take a sheet and tick something. Curious to as what it was, I inquired. “Oh, these are just the lessons I need to teach you all. Since I teach multiple classes, I keep forgetting.”, she said, showing me a sheet with a list of check-boxes.
The kid in me was fascinated. I went home and made similar lists for the subjects I was studying. It’s been a decade, but this practice stuck with me through school, university, work, and even writing.
The client said a sugar-coated No.
“This solution looks promising but let us get back to you. The investment of deploying this solution might be a bit too high.”
I was disappointed. We all knew what that eventually means.
How could we not think of it? We were over-focused on the accuracy and performance of the solution, we ignored the infrastructure costs.
That is when I realized I need to learn and apply traditional image processing techniques that don’t demand a lot of computing and infrastructure cost as much as advanced machine learning approaches but still delivers performance to an…
This was the mail I’d been waiting for. It was a familiar name in my inbox, and I was over the moon. This was what I’d been working hard for. I opened the mail... and I stared.
Earlier that day, I was handed in the project for my first data science internship.
“Arunn, here’s the project on hotel room pricing you’d be working on. Please have a look at the problem statement document and I’ve mailed some starter codes. Take the rest of the day off, and let me know if you’ve got any questions.”
“Sure, I’ll get started right…
One of my oldest friends called me up for advice, having started learning data science. He wanted to switch his field. I ended up having a lengthy conversation with him about my experience around what worked for me.
It was evident he was overwhelmed by the ton of resources available online and wanted to hear trusted information from someone who had successfully broken into data science.
While I was truly humbled, he chose to ask me for advice; I realised there could be many who don’t have a source of reliable information and could benefit from what I told him.
People hire people. Companies don’t.
I realized I’d be graduating from college soon. I wasn’t sure what’s next. I’ll need a job, I decided. Data Science seemed to be cool. I started applying online. I figured the more companies I applied to, the better my chances of getting noticed.
Bulk applying is a numbers game. I need to put myself out there for every opportunity that gets listed. I didn’t have the time to tailor cover letters and CVs for every job, so I’d use the same generic one for all. After all, it’s got everything about me.
Let me guess: As a data scientist, you love exploratory data analysis. You love unfolding insights from the data. You love reporting these insights, to see your not-so-technical manager in awe. I love that too.
No matter how much we love doing it, there’s only some amount of time that we can spend on exploratory data analysis (EDA). Beyond EDA, we have feature engineering, model development, deployment, and more to do in the data science lifecycle.