REPOGEO REPORT · LITE

rbhatia46/Data-Science-Interview-Resources

Default branch master · commit 38536fb8 · scanned 6/23/2026, 7:17:53 PM

GitHub: 3,396 stars · 761 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface rbhatia46/Data-Science-Interview-Resources, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition README's main heading and first sentence to clarify purpose

Why:

CURRENT

# Data-Science-Interview-Resources

**Update : Drawing from extensive experience in interviews over the past few years, I recently decided to launch a dedicated channel...

COPY-PASTE FIX

# Data-Science-Interview-Resources: A Curated List for Data Science & Machine Learning Interview Prep

This repository provides a comprehensive and frequently updated list of resources to help you prepare for Data Science and Machine Learning interviews.

highhomepage#2
Add YouTube channel as repository homepage
Why:
COPY-PASTE FIX
```
https://www.youtube.com/channel/UC2vHbm_9kzjrRamX8ArGdkA
```

mediumreadme#3

Integrate the 'highly curated' differentiator into the README's introduction

Why:

CURRENT

First of all, thanks for visiting this repo, congratulations on making a great career choice, I aim to help you land an amazing Data Science job that you have been dreaming for, by sharing my experience...

COPY-PASTE FIX

Unlike generic platforms or books, this collection is highly curated, offering direct answers, specific problem links (e.g., LeetCode), and company-wise questions across the full spectrum of data science interview topics.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface rbhatia46/Data-Science-Interview-Resources

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Cracking the Coding Interview

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Cracking the Coding Interview · recommended 2×
LeetCode · recommended 2×
Towards Data Science · recommended 2×
Glassdoor · recommended 2×
Ace the Data Science Interview · recommended 1×

CATEGORY QUERY
Seeking comprehensive guides and resources for data science interview preparation.
you: not recommended
AI recommended (in order):
1. Cracking the Coding Interview
2. Ace the Data Science Interview
3. StrataScratch
4. LeetCode
5. DataCamp
6. Towards Data Science
7. Glassdoor
8. Blind
AI recommended 8 alternatives but never named rbhatia46/Data-Science-Interview-Resources. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find common machine learning and AI interview questions?
you: not recommended
AI recommended (in order):
1. Cracking the Coding Interview
2. LeetCode
3. Glassdoor
4. Towards Data Science
5. GitHub Repositories
6. InterviewBit
7. Kaggle
AI recommended 7 alternatives but never named rbhatia46/Data-Science-Interview-Resources. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of rbhatia46/Data-Science-Interview-Resources?
pass
AI did not name rbhatia46/Data-Science-Interview-Resources — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts rbhatia46/Data-Science-Interview-Resources in production, what risks or prerequisites should they evaluate first?
pass
AI named rbhatia46/Data-Science-Interview-Resources explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo rbhatia46/Data-Science-Interview-Resources solve, and who is the primary audience?
pass
AI did not name rbhatia46/Data-Science-Interview-Resources — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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rbhatia46/Data-Science-Interview-Resources — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite