CEO & Founder @CoderFarm | Insurance to Your Project's Success by Providing Specialized Developers & Dedicated Support | React JS & Node JS Resource Augmentation

👋 Hi, I’m Dheeraj — Founder | Builder | Hiring Optimist
🚀 What I’m Building
I’m creating a remote hiring platform for IT startups to find developers who truly align with their mission — not just their tech stack.

Think:
✅ Culture-fit > Resume
✅ Shared vision > Transaction
✅ Purpose-driven matches > Just skills

🔍 Why This Matters
🎓 It started in 2013...
At my first campus interview, I saw hundreds of students chasing jobs they didn’t understand — driven by fear, not clarity.
That’s when I asked:

“How can you choose a job if you don’t even know what it’s about?”

Later that year, I lost my father in a car accident. I was 19.
That grief made me fearless. I promised myself to build something that helped others.

💼 17 Jobs Later...
I worked at 17 companies — searching for a team I aligned with.
I never found it. So in 2019, I started my own agency with my wife.
We even built a mud-walled, nature-filled office.

Clients came — Canva, SmartData, IIT Roorkee — but I saw the same old hiring problems:

Resume obsession

No curiosity

Misaligned teams

💡 The Turning Point
In 2023, I tried to solve it. Built an internal team. It failed.
Why? They weren’t aligned with the mission.

“You can’t build culture without the right people.”

I started studying hiring deeply — from books to behavioral psychology — and built a system focused on:
✅ Curiosity
✅ Culture-fit
✅ Honest work

It worked.

🛠️ Now, I'm building…
A remote staffing platform where:

Startups find developers aligned in purpose & values

Developers find work that fits their mindset

Both sides are matched based on real compatibility, not just keywords

✨ Features: culture-fit filters, real feedback, purpose-based profiles, and a trust-driven reputation score.

🙏 What I Need
I’m in the ideation stage, and learning from founders like you.
If you’ve ever struggled to build a team that cares — let’s connect.

Thanks for reading 🙏
Let’s build something better than job portals — something with heart.

Dheeraj Khandare

🔥 The HR Meetup That Changed How I Think About Hiring

Last week, I attended an HR meetup in Indore with 50–60 HRs — and the insights shared by the panelists were powerful.

Special thanks to Siddharth Sharma for inviting me.

A big thank you to
 👉 Swapnil Jain
 👉 Harmeet Chhabrra,
 👉 Suyesh Sabnani,
 👉 Shweta Joshi, and
 👉 Sandeep Pandey

 for sharing honest, eye-opening truths about today’s talent mindset, culture, curiosity, uniqueness, and value creation.

I’ve compiled all the key lessons, mindset shifts, and the product ideas this meetup sparked for Coderfarm in my latest newsletter.

 And as a small gesture…
 👉 All HRs & company owners who attended the meetup will get their first hire on Coderfarm completely free.

If you’re in HR, hiring, or managing teams — this edition is worth reading.

📩 Read the full newsletter:
 https://lnkd.in/duH6gYCC


#HRMeetup #HiringInsights #Recruitment #CultureFit #FutureOfWork #HRCommunity #TalentAcquisition #IndoreEvents #StartupLife

Talks about #nodejs, #reactjs, #leadership, #remotedevelopers, and #extremeprogramming

I help you hire developers who match your tech stack, values & working style — so they perform better, stay longer & feel like part of the team from day one.

Day 1 of our 90-Day Challenge is in the books. We're building a new platform to connect clients, agencies, and freelancers, and we're documenting the entire process.

Today's focus: The landing page (now 90% complete in We-web flow) and defining the UI for our three distinct user portals.

My biggest takeaway from Day 1: Talk to your users immediately.

After just a few interviews, I realized our main value proposition was off. We're pivoting the headline from "Find developers who truly fit your culture" to "Find developers who are truly interested in what you are doing". It’s a small change in words but a massive shift in perspective.

Tomorrow's goal: Making the sign-up and login functional.

I'm sharing the full (and unfiltered) update in the video. What do you think of the new headline?

#BuildInPublic #StartupJourney #90DayChallenge #Wewebbflow #SaaS #UserFeedback #Founder

Sharing what I learned from the HR community this week and how it’s inspiring new features on our hiring platform.

DataShip

Saved 56 hours per week in dashboard manual updates by building an automated ETL pipeline in Python that synced data from multiple Google Sheets into structured Looker Studio dashboards.

Saved thousands in accounting fees with a real-time Looker Studio dashboard on GCP that automated daily bonus payouts.

Identified $3,000 verified in bonus payouts surfaced by a conversion tracking framework that connected mentee milestones to incentive rules, improving payout accuracy and leadership confidence in program data.

Reduced average time-to-interview for job-seeking clients by 1 week by optimizing funnel tracking, which expanded sales team capacity to enroll new clients and scale revenue.

Improved attribution accuracy by deduplicating events across systems, ensuring mentor bonuses and client progress metrics were tied to verified, business-critical outcomes.

Marketing Data Analyst

LendingClub

- Used Python to automate data cleaning for misspelled text-based user-input for a 2 million row dataset, cutting data-cleaning time and increasing data accuracy by 24%

- Used SQL to create reports on financial KPIs like Debt-to-Income Ratio, Default Rate / Charge-off Charge-offs by Loan Grade / Risk Tier, and Weighted Average APR, enabling leadership to assess business health in real time.

- Performed Customer segmentation analysis to identify borrowers with positive CLV to optimize marketing team optimize ad targeting.

- Created interactive data visualizations with Python's Pyplot & Bokeh for stakeholder assess exposure to risk.

- Performed Credit Risk analysis to show Borrowers to reveal which income buckets had the most and least chance of defaulting.

- Diagnosed inefficiencies in the underwriting pipeline and flagged missing predictive variables using statistical correlation analysis.

- Recommended reallocating marketing spend towards these high-density states to improve customer acquisition efficiency and lower CAC.

Growth Analyst - Freelance

School of Public Policy & Administration, Carleton University

Used Excel and R to process, clean, and analyze a dataset of over 1,600 observations from the 2011 New York Housing Vacancy Survey.

Designed and executed a study to assess the impact of affordable housing policies in New York City, leveraging the 2011 New York Housing Vacancy Survey.

Used Partial Linear Machine Learning Model to show a 59% decrease in rents in rent-controlled housing compared to non-rent-controlled housing, highlighting the impact of rent-control policed in New York.

Delivered insights to stakeholders on rent stabilization, highlighting its benefits and trade-offs to guide housing policy decisions.

Tech Stack: Excel, Stata, R, Data Visualization, Quantitative Analysis, Double Debiased Linear Regression, Statistical Analysis, Statistical Inference, Supervised Machine Learning for Research.

Quantitative Analyst

Used Excel & Stata to create data visualizations to help analyze the relationship between unemployment and inflation in the United States spanning over 50 years (1970-2023).

Demonstrated the flattening of the Phillips Curve, indicating a weakened relationship between inflation and unemployment, thus limiting the effectiveness of expansionary fiscal and monetary policies to reduce unemployment during recessions.

Presented findings to professors and peers in the economics faculty, contributing to discussions on the evolution of monetary policy and its impact on unemployment and inflation.

Research Analyst

Elite Traders University

Performed A/B test for email subject lines for Financial education program resulting in an increase in Click Thru Rates and open rates by 30-50% leading to an increase in booked calls for sales team.

Designed and executed a marketing strategy in 10 days for a new financial education digital product that generated $1988 in revenue in 15 hours after performing market research on our ideal customer avatar.

Developed a re-engagement email sequence campaign to boost open rates. After implementing re-engagement email sequence open rates went from 10% to 17%

Non-Skiils: Copywriting, Email copywriting, Content writing, Sales, story telling, presenting insights.

Abubakar Al-faki

Helping Digital Marketers increase their Bottom Line, by focusing on closing inbound leads on Sales calls on High Ticket Offer. Allowing them to focus more on improving and running their business.

Further Qualifying leads to see if they are a good fit for your offer so you get more committed clients and higher retention

High Ticket Closer™

Scale your ad ROI by at least 10% using Google's Conversion Tracking system. (GT4 + GTM + stape.io)

I help you match sales from their CRM/payments processor to your ads managers data using Google's Conversion Tracking System, so you know which ads to scale.

Connect & DM me to book a free consult.

𝗪𝗵𝗮𝘁 𝗜 𝗰𝗮𝗻 𝗱𝗼 𝗳𝗼𝗿 𝘆𝗼𝘂

𝗕𝘂𝗶𝗹𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 𝗵𝗼𝘀𝘁𝗲𝗱 𝗼𝗻 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺
→ Daily refreshed Looker Studio reports pulling data from Ads Manager, Shopify, or CRMs automatically without manually exports or imports.

𝗗𝗲𝗳𝗶𝗻𝗲 & 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗸𝗲𝘆 𝗲𝘃𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝘀 𝗶𝗻 𝗚𝗧𝗠 + 𝗚𝗔𝟰 (e.g., Product Page view, page scroll, add to cart, checkout, purchase).

𝗦𝗲𝘁 𝘂𝗽 𝗮 𝗦𝗲𝗿𝘃𝗲𝗿-𝗦𝗶𝗱𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗚𝗧𝗠 + 𝗚𝗔𝟰 𝘄𝗶𝘁𝗵 𝗦𝘁𝗮𝗽𝗲.𝗶𝗼  
→ Match sales across platforms, deduplicate, and apply clear attribution rules so you know which channels are driving the most profit.

𝗨𝗻𝗶𝗳𝘆/𝗯𝗹𝗲𝗻𝗱 𝗮𝗱 𝗺𝗮𝗻𝗮𝗴𝗲𝗿 + 𝘀𝗮𝗹𝗲𝘀 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗢𝗻𝗲 𝗟𝗼𝗼𝗸𝗲𝗿 𝗦𝘁𝘂𝗱𝗶𝗼 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱  
→ Combine Google Ads, Meta Ads, and Shopify/Stripe data for accurate ROAS, CAC, and LTV in your dashboard, so you know which ads and channels are actually driving profitable Customer acquisition.

𝗙𝗶𝘅 𝗯𝗿𝗼𝗸𝗲𝗻 𝗼𝗿 𝗶𝗻𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴  
→ Troubleshoot GA4, GTM, and ad platform mismatch in KPIs so you can trust your numbers.

The post iOS14 has made marketing data across platforms inaccurate because people don’t accept cookies.

When you work with me, we can 
- Fix Mismatch in sales & conversions across ad platforms.
- Lower your CAC by stopping ads that aren't profitable.
- Increase your ad ROI by at least 10% using Google Conversion Tracking System.

𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝗜 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵
- E-Commerce & DTC Brands
- Digital Products & SaaS
- Info Products

𝗦𝗸𝗶𝗹𝗹𝘀
- Marketing Data Analytics
- Data Visualization in Looker Studio
- ETL/ELT with Python
- Conversion Tracking & Attribution
- GTM + GA4
- Server-side tracking with Stape.io

𝗧𝗼𝗼𝗹𝘀
Python • Looker Studio • Google Sheets • Excel • SQL  • GA4 • GTM • Google Cloud Platform

Hate updating client data because it means losing the old version?

I was working with a client that runs a data mentoring program who wanted to build a Bonus Payout System that processes upto $42,000 a month.

When a new client is Onboarded the client can have more than one mentor
    - One mentor to help with Technical Skills
    - One Mentor to help with Interview Skills

This is a One-to-Many relationship
    - One client can have multiple Mentors.

To compound the problem, a client can request a different mentor at any point in time.

These changes are not recorded and backed up. They are just overwritten.

This means no historical record of changes to mentors of any client.

There is a bonus called "Placement Bonus", which is given to the Mentor who works which the client till they land a job.

If both mentors worked with the client till placed, then we give the bonus to the mentor who worked with the client the longest.

Without keeping a historical record of changes to a clients mentor, we won't know who worked with the client the longest.

The Solution is to build an SCD Type 2 (Slowly Changing Dataset)

When a clients' mentors are changed we keep the old row and create a new row with the updated mentor columns.

This allows us to see the full history of changes in mentors for client.

So we can see which mentor worked with the client the longest and give payout the bonus automatically.

This process is All Automated.

Automated using an ETL pipeline hosted on Google Cloud Platform.

Google Cloud Platform allows you essentially rent a computer to run an ETL or anything based on a schedule or real time.

The use cases for building SCD Type 2 are numerous

- Detect when a user’s engagement starts to drop → trigger reactivation campaigns.
- Detect when customers become “inactive” and trigger reactivation campaigns.
 - Build customer lifecycle models: New → Engaged → Buyer → Promoter.
See how long it takes for a Customer to move from your Free to Paid Products.

I love building these type of automated Data Models for clients.

It saves so much time and you get a historical record of behaviours or statuses of your clients you want to track.

Costs depend on the Size of your Dataset.

For my Client costs less than $2 a month.

If you want a system like this implemented for you 
Comment "Update" and I will reach out to you.

Most Linkedin Info product creators don't track these metrics

The last metric costs them sales and higher conversions

1. Free-to-Paid Conversion Rate
     -- How many of your free tier customers becoming paying customers
     ----- This allows you to how many Free tier customers u need to get 1 paying customer.

2.  Sales Page Conversion Rate (Landing Page %)
% of visitors who land on your sales page and buy.

3. Linkedin Post Conversion rate
    -- How many people that follow your CTA to your sales page, booking page convert to Paying customers, email subscribers etc

There is currently no easy way to track Point Number 3

And I would argue it is one of the most important metrics to track and optimize.

LinkedIn is your Top of Funnel.

it's the Engine that feed tour business with leads and customers.

Not optimizing this is costing you money.

- Not all posts will generate the same revenue and conversions.
- More views doesn't necessary equal More Money.

In some cases posts with less views make you more money.
Because it speaks more to your ideal customer than "viral" posts.

I am currently thinking of building a Guide on "How to Track Linkedin Posts that make you the most money"

If a 100 creators comment "Track",  I will make the guide.

taplio

The Battle

Dheeraj Khandare

Abubakar Al-faki

Followers

Posts

Engagements

Likes

Performance ScoreDheeraj Khandare's LinkedIn Performance

Performance ScoreAbubakar Al-faki's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Dheeraj Khandare

Abubakar Al-faki

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Dheeraj Khandare's LinkedIn Performance

Performance ScoreAbubakar Al-faki's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDheeraj Khandare's LinkedIn Performance