Hari Prasad Renganathan

Take-Two Interactive Software, Inc.

Data Scientist

• Contributed to 4 major Enterprise Data Science/ Analytics projects in the Sales team
• Collaborated with ML Engineers and Data analysts to deploy price elasticity outputs from AWS S3 buckets into production as an interactive dashboard using Dash
• Optimized sales-forecasting model by introducing ARIMA and improved performance by 33%
• Mined and analyzed data of 72 different companies to perform competitive analysis using hypothesis testing leveraging Snowflake, SQL and Tableau
• Performed market research of company’s 12 subsidiaries and presented the patterns to Marketing department

Data Science Intern

MyRealProduct

MyRealProduct is a 4-week cohort where aspiring Data and AI professionals build real, usable products instead of just toy projects, solving real-world problems across domains like healthcare, food, and productivity.

Mentor | Instructor

NYC Women in Machine Learning & Data Science 

Guest Speaker

The College of Westchester

ElevenLabs

Judged Voice AI Hackathon sponsored by ElevenLabs & conducted by Quru AI

Technical Judge

Globee Awards

Industry Judge

Google

I was invited as a speaker at the AICamp event, hosted at Microsoft NYC and sponsored by Google.

The energy in the room was electric! I dove deep into the world of AI content creation and explored practical ways to make AI writing sound more human. The engagement and questions from the audience were incredible - clearly this is a pain point many of us share.

Automate Apply

Delegate Applying For Jobs! Hire a Personal Assistant who can apply jobs on your behalf.

Angel Investor

BrowserStack

I was invited to give a speech at the BrowserStack event on "ML Model Testing & Validation."

When you think about model testing, what comes to mind?
Train-test split? 
Accuracy? 
Confusion matrix?

Yes! But model testing is more than just that.
It's about prioritizing business requirements and ensuring the model aligns with them.

I spoke about the importance of incorporating business context into model testing.

JotterWolf

Struggling to track your job applications?

JotterWolf addresses the common challenges associated with job applications and interview preparation. It offers the following benefits:
- Automated job application tracking
- Interview preparation support through ChatGPT extension
- Goal-setting functionality for maintaining job search momentum

Co-Founder

Associate Data Scientist

Leaving the US soon 🇺🇸 
America taught me how to dream 
.....and then asked me to leave.

Every year, thousands of skilled immigrants pray for one email.
Not a job offer. Not an approval.
Just an entry in a lottery.

Because in the U.S., your career can depend on a random draw
Not your talent.

I’ve spent the last 4 years:
✅ Graduated from Columbia University
✅ Worked as a Data Scientist at a top gaming company
✅ Built products that saved hundreds of hours for global teams
✅ Mentored 700+ students to break into AI
✅ Co-founded a startup empowering job-seekers

But none of that mattered when the H-1B lottery said, “Not selected.”
Three times.

It’s strange
the country that taught me innovation still runs on a system of chance.

Every time a builder leaves, America doesn’t just lose a visa holder.
It loses a product.
It loses a mentor.
It loses a dream that could’ve been built here.

But here’s the truth I’ve learned:
📌 A visa can expire.
📌 A job can end.
📌 But your ability to build never leaves you.

So yes, I’m leaving the U.S. soon.

Not because I failed.
But because I refuse to let luck define my life.

Wherever I go next
I’ll keep building, teaching, and creating opportunities.

Because talent shouldn’t need a lottery to belong.

To everyone waiting for that one email
-- You’re not unlucky.
-- You’re just temporarily unrecognized.
Keep building anyway. 💙

Leaving the US soon 🇺🇸 
Not because I failed, but because the system did.

I came to the US 4 years ago with a dream
To study, build, and create something meaningful.

In these years, I’ve graduated from Columbia University,
worked as a Data Scientist at Take-Two Interactive,
and built multiple AI products used by global teams.

I’ve co-founded a startup, mentored 750+ students through MyRealProduct,
and helped people go from tutorial hell to building real products.

And yet, despite all that, I may soon have to pack my bags and leave.

Not because I want to.
But because after 3 H-1B lottery rejections,
the system tells me luck matters more than impact.

This country gave me everything:
a world-class education, 
incredible opportunities, 
and lifelong connections.

But it also taught me how fragile a “dream” can be when it depends on a random draw.

I’ve seen brilliant people: Engineers, Data scientists, Designers, leave not because they lacked talent,
but because they didn’t get picked.

And every time one of us leaves, America loses another builder.

But here’s what I’ve learned:
-- Your value isn’t tied to your visa status.
-- Your curiosity, resilience, and ability to build travel with you.

If you built something once,
you can build it again (anywhere).

And I will.

Whether in the UK, India, or somewhere else
I’ll keep building, teaching, and helping others break into AI before AI breaks them.

To every international student or immigrant reading this
You’re not alone.
You’ve already beaten the odds once by getting here.
You’ll do it again, wherever you go next.

Because you’re not leaving your dream.
You’re just taking it somewhere new.

P.S.
I’m Hari Prasad Renganathan
a Data Scientist at Take-Two, Instructor at MyRealProduct, and builder of AI tools like JotterWolf.
If you’re an international student or builder navigating your next step,
follow along.
We’ll figure it out together.

I got my first job at 21, earning ₹10,000/month (~$110).

At 22 → $5,000/month
At 23 → $6,500/month
None of this came from my full-time job.

When I was 20, I felt dumb.
9.3 GPA, but no skills.
I wouldn’t have hired myself.

I had two options:
-- Cry about it.
-- Or do something.
So, I did something.

I learned everything: video editing, digital marketing, branding.
Worked on unpaid gigs just to learn.
Failed at everything.

But too scared to give up.

Then I found Python and Data Science.
Except 
who’d hire a Mechanical Engineer trying to be a Data Scientist?

No choice. I cold-DM’d 200+ people on LinkedIn:
“I’m a good Python developer. I can help you with Python.”
No replies.
 
Until one founder did.
He asked me to create a teaching plan for kids.
I did. He liked it.

Asked, “What’s your salary expectation?”
Me (mind-voice): “Wait, you're paying me? 👀”
Me: “10–15k rupees?”
He said, “Done.”
That was my first win.

If someone like me, who started coding at 20, from Mechanical Engg
can become a TEDx speaker, Ivy League grad, and Data Scientist…

Why can’t you?
The only thing I never did was give up.

👋 Dear 22-year-old me,
Stop applying everywhere.

You’re wasting hours sending resumes into black holes.

Here’s what I wish I did instead 👇

1️⃣ Follow the money

Every week, check which startups raised funding. 
They’re growing, hiring, and overwhelmed. 
Perfect time to reach out. 
(Hint: Crunchbase, Ycombinator jobs, LinkedIn VC pages, TechCrunch funding news)

2️⃣ Find the decision-makers

Don’t message HR. Message founders, tech leads, or hiring managers. 
These are the people who feel the hiring pain and can actually say “yes”.

3️⃣ Do your homework

Before sending a message, learn what the company does. 
Mention something specific you liked:
A product feature, design choice, or customer problem they solve.

4️⃣ Pitch value, not desperation

Instead of “I’m looking for opportunities”, 
Write “Here’s how I can improve X metric or automate Y process for your team.”
Show them ROI, not your resume.

When I was looking for a job, I was rejected everywhere.
So I stopped applying.

I texted 100 founders. Told them how I could help.
And got multiple offers.
No job boards, no referrals.

Opportunities rarely show up in your inbox.
You have to create them.

📌 Save this post for later
🔁 Reshare this to your community

Stop wasting months learning SQL the wrong way.

If your goal is to land a high-paying job in 2025
Skip the random YouTube rabbit holes.

Here’s the truth 👇
Most beginners spend months learning SQL syntax…
But still blank out in interviews.

Why?
Because they study everything, except the 10% that actually gets them hired.

So if you’re aiming for roles like Data Analyst, Business Analyst, or Data Engineer,
focus only on what matters.

SQL Topics That Recruiters Actually Care About:
-- SELECT, WHERE, ORDER BY, GROUP BY, HAVING
-- JOINS: INNER, LEFT, RIGHT, FULL
-- CASE, IF, NULL, IN, BETWEEN, LIKE
-- SUBQUERIES
-- WINDOW FUNCTIONS (ROW_NUMBER, RANK, LEAD, LAG)
-- CTEs (Common Table Expressions)

Interview Problems You’ll Definitely See:
-- Find 2nd highest salary
-- Count active users in last 7 days
-- Identify duplicate rows
-- Running totals using OVER()
-- Compare employee salary vs team average
-- Calculate user growth or churn over time

Resume Tip:
❌ “Proficient in SQL”
✅ “Queried 50K+ customer records to find churn patterns using window functions & time-based filters.”

🔥 Learn smart, not slow.
❤️ Like = You’re done wasting time
🔁 Repost = Someone in your circle needs this
👤 Follow Hari Prasad for more data & career tips

Credits: Heena Kouser's post inspired me to share this. If you are not following her yet, you should.

When I got 9.3 GPA in college, I was upset — because it wasn’t a perfect 10.
When I got 96% in Class 12, I was upset — because it wasn’t 99%.
When I didn’t get into IIT, I was upset — because I thought my career was over.
When I got rejected in every job I applied to, I was upset — because I thought I wasn’t good enough.
When I moved abroad with $88k student loans, I was upset — because I didn’t know if I could make it.

But looking back, I’m grateful for every one of those moments.

Every “no” forced me to find a better “yes.”
Every rejection gave me redirection.

✅ Working as a Data Scientist at one of the biggest gaming companies
✅ Graduated from an Ivy League University
✅ Built multiple AI products and worked with 5+ startups from 0 to 1
✅ Co-founded startups that reached 15,000+ users
✅ Built a 40K+ community on Linkedin
✅ Featured on BBC, TEDx, Times Square
✅ Invited to speak at big tech events & conferences

…and this is just the beginning.

If you’re in that phase where nothing seems to be working, hang in there.
Your time will come.
Just don’t stop showing up.

I’ve reviewed 800+ resumes in the last year
Here’s why most of them get rejected in 5 seconds.

After mentoring 10k+ job seekers, 
I keep seeing the same resume mistakes that instantly kill your chances.

Let’s fix that 👇

Problem 1: “Skill Overload Syndrome”
-------------------------------------
People list every tool they’ve ever touched: Python, R, SQL, Power BI, TensorFlow, PyTorch, Excel, and 25 more.
Recruiters don’t care how many tools you “know.”
They care what you did with them.

✅ Instead: Show 3–5 tools tied to results.
E.g., “Optimized marketing ROI by 18% using Python + SQL dashboards.”

Problem 2: Responsibilities ≠ Results
-------------------------------------
“Developed machine learning models.”
Cool. So did 1,000 other applicants.

✅ Instead: Add impact.
“Deployed churn prediction model that saved $120K in retention costs.”

Problem 3: The ‘Final Year Project Dump’
-----------------------------------------
I see 5 academic projects but zero business outcomes.
If your resume reads like a Kaggle profile, it’s a red flag.

✅ Instead: Write about projects that solved real problems
Like automating reports, improving accuracy, or saving time.

Problem 4: No Narrative
-------------------------
Your resume should tell a story, not just list stuff.
“Who are you?” → Data Scientist? Analyst? ML Engineer?
If I can’t tell that in 5 seconds, you’re out.

✅ Instead: Start with a 2-line summary showing your direction + impact.

💡 Here’s the truth:
Resumes don’t get rejected because you lack skills.
They get rejected because you fail to communicate impact.

If you’ve been ghosted after 100s of applications, your problem isn’t “luck.”
It’s messaging.

Save this post if you found it useful.
And follow me Hari Prasad Renganathan I share no-fluff insights on AI, job search, and building a product-driven career.

Most people pray for a job.
But very few pray for a healthy culture.

A job gives you a salary.
A culture gives you respect, growth, and peace of mind.

You can survive in a toxic team for a few months…
but you thrive in a culture that values you.

So the next time you’re manifesting a new role,
don’t just ask for the title or the pay 
ask for a place where:
✅ Your voice is heard
✅ Your manager trusts you
✅ You’re allowed to grow without guilt

Because the wrong culture can drain you faster than the wrong job ever will.

💭 The goal isn’t just to get hired. It’s to stay happy where you’re hired.

What’s one non-negotiable you look for in a company culture? 👇

Make it a habit to respect people

Not because of their title.
Not because of their qualifications.
But simply because they’re human.

I’ve seen people treat someone differently once they know their position or achievements.

And that says a lot.

The real test of character is how you treat people who can’t “do” anything for you.

Respect is free. But it reveals everything about you.

"Data Analytics is dead."

This hurts.

As someone with a Master’s in Data Science
and 4+ years of experience as a Data Scientist,
if someone tells me “everything you’ve done is dead”

It stings.

But it’s not dead.
It’s just become efficient.
In other words, it’s getting automated.

I’ve spent the past 2 years building an AI that can do what I used to do.

And honestly, this isn’t new.
-- Mathematicians didn’t disappear when calculators came.
-- Designers didn’t vanish when Figma arrived.
-- Writers didn’t die when ChatGPT showed up.

They evolved. And so did their roles.

Today, data analytics is no longer a technical skill 
It’s a subject-matter expertise.

Tomorrow, you’ll use AI + your domain expertise (Data Analytics) to analyze data faster, better, and smarter.

You’re not replaceable, unless you refuse to evolve.

What do you think?
Share this with your data community. Let’s evolve together.

PS: I help Data Analysts learn AI through a hands-on workshop.
If that’s you, comment your email 👇 or DM me “workshop” and I’ll send the details.

My LinkedIn tells you that I am a successful Data Scientist working in the US 🇺🇸 & living the dream

But here’s what it won’t tell you:

► My college didn’t allow me to sit for tech placements 
Because I didn’t have a CS degree.

► Many Tier-3 US universities rejected my master’s application
Because I hadn’t taken core CS courses like Data Structures or Algorithms.

► When I started writing LinkedIn posts and Medium articles on Data Science, people commented:
“Who are you to talk about this? You’re not qualified.”

► I applied daily for 5 months (200+ applications) and didn’t get a single interview call.
No experience. No referrals. Just rejection after rejection.

But I kept building.
Projects turned into products.
Rejections turned into opportunities.
And slowly, the story changed.

3 Lessons I learned the hard way 👇

💡 1. You don’t need permission to start.
Your college, degree, or background doesn’t decide your future.
Your consistency does.
No one gave me a chance, so I built my own.

💡 2. Do the work when no one’s watching.
I wrote posts that got zero likes.
Applied to jobs that never replied.
But every single day of showing up made me a little better than yesterday.

💡 3. Build, break, repeat.
Most people wait until they’re “ready.”
But you only get ready by building, failing, and fixing.
Perfection comes after action, not before it.

Failures weren’t signs that I didn’t belong.
They were proof that I was getting closer.

4 months.
Not a single internship.

Meanwhile, my classmates (already working professionals) were bagging offers left and right.

At one point, I almost gave up.
But then a thought hit me:
“If I can’t beat them at their game… I’ll create my own.”

So, one night, I opened LinkedIn.
No automation.
No fancy scripts.
Just raw hustle.

I searched for founders in New York, opened each profile, and sent this message:
“Hey, I’m a grad student working in Data. I’d love to intern with you this summer.”

100 messages. One by one.
Next morning: I woke up to 10 interviews lined up.

Too good to be true?
Even I couldn’t believe it.

Truth is, I didn’t even know what half these startups did when I texted them.
So before every call, I’d study their product, sign up, find 3 ideas, and pitch them like I’d already been part of their team.

Some said, “We’re not hiring.”
Some said, “Maybe later.”
But a few said, “Let’s talk.”

And one of them… really meant it.

They were so impressed, they offered me $40/hour
More than what even top tech companies were paying interns that year.

For the first time, I felt what it’s like to be seen.

A few weeks later, I got more offers and had to choose another company.

But I didn’t want to leave them hanging.
So I referred my friend (who’s amazing at what she does).
She got the role and the startup was thrilled.

That day I learned something schools don’t teach you:
-- Jobs aren’t always found on job boards.
-- Sometimes, you have to create your own.

If you can’t find a job, create your own.

Follow me (Hari Prasad Renganathan)
I’ll share the other “crazy” things I did that landed me jobs nobody was hiring for.

You should be the dumbest person in the room.

It took me years to really understand this.

In school, we were rewarded for having all the answers.
In college, we were praised for topping the class.

So, I kept chasing that.

I graduated with a master’s in Data Science from Columbia.
Helped 5+ startup products.
Helped 750+ students learn AI.

On paper, I was doing great.

But then I entered rooms full of real builders.
People who had built companies, shipped 10+ AI systems, and managed teams way smarter than me.

That’s when it hit me.

My degree didn’t matter.
My past projects didn’t matter.
My ability to learn fast from others did.

The first few moments were uncomfortable.
Asking questions felt awkward.

Admitting “I don’t know” was harder than debugging an LLM agent at 2 a.m.

But every time I leaned into that discomfort, I grew faster than ever before.

If you’re always the smartest person in the room,
You’re in the wrong room.

Be the dumbest builder instead 
That’s how you evolve the fastest.

Repost if you believe humility is the real growth hack.

You’ll never forget the people who took a chance on you when everyone else overlooked you.

I still remember every recruiter, manager, and mentor who looked past my career gaps and imperfect background 
and gave me a shot to prove myself.

They didn’t just hire a resume.
They invested in potential.

And that changed everything
Every role I landed, every project I built, every step I grew.

Because in the end, people hire people.
Not bullet points. Not GPA. Not degrees.

Yes, skills and credentials matter, but they’re never the full story.

Sometimes, it just takes one person to see your value and it can change your entire life.

Be that person 🙌

PS: Credits to Jean Kang for inspiring me to write this.

I’m on a mission to create 365 AI Engineers in the next 365 days.

And I’m dead serious about it.

For the past 2 years, I’ve been learning, building, and teaching AI.

I’ve helped hundreds of people:
✅ Build their first AI project
✅ Write their first line of code
✅ Land their first job

Now, I’m launching this FREE newsletter to help you break into AI - step by step, from beginner to AI Engineer.

If you don’t become an AI Engineer in the next 365 days with the materials I share…. you can unfollow me.

Join here: https://lnkd.in/eveg5apm

💌 First newsletter drops this Sunday.
Until then, check out the AI news I’ve shared before and get ready.

Share it with a friend who’s ready to start their AI journey.
Let’s grow together.

If you can’t answer this question in 30 seconds, you’re not ready for the interview. 

“Why should we hire you?”

It’s one of the simplest interview questions…
yet it knocks out more candidates than any coding challenge ever could.

Most people go blank or default to clichés like:
 ❌ “I’m a hardworking, passionate team player”
 ❌ “I’ve always dreamed of working here”

None of that tells the recruiter what they actually need to know.

When they ask “Why should we hire you?”, what they’re really asking is:
 👉 Do you get what this role needs?
 👉 Can you prove you’ve done something similar before?

So here’s how to flip the script and stand out 👇

Step 1: Show a real result.

Don’t say “I’m a fast learner.” Say what you learned fast and how it helped your team.
💬 “At my previous job, I automated a manual reporting process and cut analysis time by 60%. I noticed this role emphasizes efficiency, that’s exactly the kind of impact I can bring.”

Step 2: Connect the dots.

Tie your story to what they care about. Mention their product, goal, or pain point.
💬 “In college, I built a data dashboard for our club that tracked engagement. I’d love to bring that same data-driven mindset to your marketing team.”

That’s it.

No buzzwords. No fluff. Just:
✅ Measurable results
✅ Clear alignment
✅ Confidence without ego

Practice this one answer until it rolls off naturally, because in most interviews, this is the question that decides everything.

Good luck with your next interview :) 

-------
Follow me Hari Prasad Renganathan for more tips!
🔁 Send this to that one friend who has an interview coming up.

Get paid for your wisdom, not your watch. 

People often ask, “Why do you charge that much for an hour?”
Because they’re paying for the decade it took me to make that hour valuable.

Here’s the truth:
-- It’s not expensive because it takes time.
-- It’s expensive because it saves yours.

Most professionals underprice themselves because they:
✅ Measure effort, not expertise.
✅ Fear losing clients by standing firm.
✅ Forget that experience compounds like interest.

So next time someone says, “That’s too expensive,”
Remember, they’re not your audience.

Your rate reflects your results, not your runtime.

Charge for the years you’ve spent getting this good.

Agree?

I asked ChatGPT to roast Data Scientists…and it did us dirty ⬇️

Warning: If you’re a Data Scientist, this post will hurt.

------------
Every Data Scientist wants to “work on AI”…
but spends half their day merging CSVs and praying the columns align.

You say “I do machine learning,” but 90% of your code is still df.dropna().

You spend weeks optimizing hyperparameters… but can’t explain your own model without opening ChatGPT.

Your Jupyter notebook has 67 cells, 5 random seeds, and zero documentation.
But yes, “production-ready.”

And don’t even start about meetings—
 🧑‍💼 PM: “What’s the ROI?”
 🧑‍🔬 You: “Depends… on the assumptions…”
 🧑‍💼 “So… you don’t know?”
 🧑‍🔬 “I do, but with a 95% confidence interval.”

We wanted to change the world with data…
but now we just change column names.

🎤 df.micdrop()

“Networking is overrated.”

Yeah, I said it.

Everyone tells you to DM recruiters, ask for coffee chats, and “build
connections.”

I did all that… 
and got ignored for months
Even with Columbia on my resume.

Then I flipped the script.

Instead of messaging recruiters, I started DM’ing directors, VPs, and founders the people who actually have the power to make hiring decisions.

Guess what?
 ✅ 10 interviews in a week
 ✅ 4 offers

No coffee chats. 
No “hope you’re doing well” intros. 
Just clarity and courage.

That story (and my 3-step DM framework) was just featured by StudyInternational.com

They called it:
 👉 “Columbia grad’s #1 secret to hunting for jobs in extremely competitive fields.”

Full story here: https://lnkd.in/enwAZUga

If you’re struggling with your job search, remember this
You don’t need more connections.
You need the right ones.

💬 Would you ever DM a company’s VP directly for a job?

The life of a Data Analyst (visualized perfectly 👇)

1️⃣ I’m excited about this new project
2️⃣ Wait… where’s the data?
3️⃣ This data makes no sense
4️⃣ Everything is broken
5️⃣ Maybe it’s not that bad
6️⃣ I see a pattern
7️⃣ They will love my insights
8️⃣ Nobody read my report 😭

If you’ve ever been in data analytics, this probably feels too real.

From chasing missing data to debugging broken pipelines only to realize your carefully crafted dashboard got… 3 views 😅

But here’s the thing:
Even if nobody reads your report, you’re still learning how to think with data.

And that’s the real skill that compounds over time.

Credits to Amney Mounir for spitting facts 👀

Taplio

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