4 Data-Driven Techniques to Secure Your Next Job in a Tough Market

Data Neighbor Podcast

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4 Data-Driven Techniques to Secure Your Next Job in a Tough Market

And How AI is Changing the Landscape

Hai Guan

and

Sravya Madipalli

Mar 22, 2025

Transcript

Trying to break into data science or land your next role but feel like you're getting lost in a sea of applicants? You're not alone—and this episode is exactly what you need. We’re joined by Karun Thankachan, Senior Data Scientist at Walmart and former Amazon Applied Scientist, who’s mentored thousands of job seekers and cracked the code to job hunting in today’s ultra-competitive tech landscape.

We get into the metrics, strategies, and mindset shifts that actually move the needle - plus a deep dive into how recommender systems work and how large language models (LLMs) are changing the game.

What You’ll Learn in This Episode:

The metrics-driven approach to job searching: How many applications, referrals, and LinkedIn connections should you aim for?
How AI is changing hiring for both recruiters and candidates
The importance of networking and why it’s the most underrated skill in data science
A deep dive into recommender systems - how AI powers Netflix, Amazon, and Walmart recommendations
How LLMs (Large Language Models) are revolutionizing recommendation engines

Some key takeaways:

The exact job search funnel you should be optimizing.
Karun breaks down a numbers-driven system: 100 LinkedIn connection requests a week, 4–6% reply rates, and 20 referral-based applications—metrics that give you a realistic roadmap and set proper expectations.
Why your portfolio and resume only get you halfway there.
Building models and showcasing them well is step one, but Karun reveals that it's your ability to generate referrals and build trust that closes the loop.
How AI is disrupting both sides of the hiring table.
Discover how recruiters and candidates are using AI tools to screen resumes and scale applications—and why that makes standing out harder than ever.
How to tailor resumes using AI—without falling into common traps.
Karun shares a clever system of creating 3–4 “template resumes” that you can lightly tweak using AI to beat applicant tracking systems (ATS) without sacrificing quality.
For mid-career professionals: how to position yourself to level up.
From data analyst to applied scientist, Karun outlines the gaps you need to fill, the stories you need to tell, and how to highlight ambiguity-handling and ownership in your experience.
Inside the world of recommender systems and how LLMs are enhancing them.
Learn how companies like Walmart, Netflix, and Amazon personalize content using multi-layered recommendation engines—and how LLMs are beginning to solve challenges like cold starts.
The most underrated skill in data? Networking.
From unlocking hidden datasets to securing referrals, Karun explains why making meaningful connections is your superpower—both in your company and in the job market.

Whether you’re an aspiring data scientist, a mid-career professional looking for new opportunities, or just interested in how AI is reshaping hiring and recommender systems, this episode is packed with insights you don’t want to miss!

Chapters:

0:00 Introduction

2:01 Karun’s Career Journey

6:36 The Science of Job Searching: Key Metrics

10:10 Optimizing LinkedIn Outreach & Referrals

16:04 How AI is Reshaping the Hiring Process

28:23 Building a Winning Data Science Resume

39:25 Recommender Systems 101

45:50 The Future of AI in Recommendation Systems

52:20 Most Underrated Skill in Data Science

Connect with Karun, Hai, Sravya, and Shane: