Web3 Job Market Research: 36.6% of job seekers are from 985/211 universities, and the acceptance rate of new graduates by "Big-Tech Companies" is less than 0.28%
BlockBeats News, July 9th, according to a BlockBeats survey, nearly 80.5% of the respondents who participated in the Web3 job-seeking questionnaire came from first-tier universities in China, including Project 985 and Project 211 institutions. Among them, 36.6% were from Project 985 universities, and 43.9% were from Project 211 or other first-tier universities. Additionally, 7.3% of the job seekers had overseas educational backgrounds, while only 12.2% were from vocational schools or other types of institutions.
Regarding their academic backgrounds, these highly educated job seekers were not lacking in options. Among the respondents who participated in the Web3 job-seeking questionnaire, 46.34% were from computer science and information technology-related majors, and 21.95% were from finance and business backgrounds. They originally had the opportunity to enter more stable traditional industries and were also competitive in mainstream industries such as large corporations, securities firms, and banks.
According to Bitget's campus recruitment data, its 2025 campus recruitment program received over ten thousand resumes. In the end, only 28 graduates were hired, entering various core business modules such as technology, product, regional growth, global branding, and global operations, covering almost the entire crypto business chain.
This survey was conducted with data provided by Bitget, interviewing over 200 practitioners. The full report has been released in an article on BlockBeats titled "2025 Web3 Job Market Report: 10,000 Applicants Vie for 28 Positions, How Can You Succeed?".
You may also like

Who is the true winner of the "Tokenization" narrative?

Moss: The Era of AI-Traded by Anyone | Project Introduction

Chip Smuggling Case Exposes Regulatory Loophole | Rewire News Evening Update

How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.

Old Indicator Fails, Three Major New Signals Emerge: BTC True Bottom May Still Be Below $60K

Meeting OpenClaw Founder at a Hackathon: What Else Can Lobsters Do?

Huang Renxun's Latest Podcast Transcript: NVIDIA's Future, Embodied Intelligence and Agent Development, Soaring Demand for Inferencing, and AI's PR Crisis
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Crypto_Trade shows how structured inputs and controlled adaptability can build a more stable and reliable AI crypto trading bot within the WEEX AI Trading Hackathon, highlighting a practical path toward scalable AI trading systems.

AI Starts to Devour the Manufacturing Industry | Rewire News Morning Edition

When Scaling Meets Speed, Ethereum Foundation Introduces "Hardness" to Safeguard the Base Layer

Google, Circle, Stripe Flock Together to Let AI Spend Money: Payment Giants' Joys and Worries in 2026 Q1

$100 Billion Factory Purchase: Bezos and Middle Eastern Capital Shift AI Money from Cloud to Shop Floor

Xiaomi and MiniMax both unleash their ultimate moves, signaling the start of the Agent Pricing War.

Predicting markets has taken the spotlight, but the Perp DEX has been quietly waging war on traditional exchanges.

Is the Market Slump Still Making Millions a Day? Is pump.fun's Revenue Real?

Understanding x402 and MPP in One Article: The Two Paths of Agent Payments

Quick Look at the Latest 18 Graduation Projects from Alliance: Who's the Next Pump.fun?

It's not just the prediction market that profits from the Iraq War
Who is the true winner of the "Tokenization" narrative?
Moss: The Era of AI-Traded by Anyone | Project Introduction
Chip Smuggling Case Exposes Regulatory Loophole | Rewire News Evening Update
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.