Channel
@ji_ys
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
1,598subscribers
+7 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002656308243 |
|---|---|
| Type | Channel |
| Username | @ji_ys |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/ji_ys |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 23:54 | 1,598 | +7 |
| 8 Aug 2026, 00:22 | 1,591 | no change |
| 7 Aug 2026, 10:46 | 1,591 | first reading |
20 posts held, back to 22 March 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
| Window | Rolling 30 days · latest post in window 20 July 2026 |
|---|---|
| Posts held | 20 (22 March 2026 – 20 July 2026) |
| Views total | 1,030 |
| Reactions total | 0 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 17:58 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
15 reactions across 5 posts, in 2 distinct kinds. The most used accounts for 93.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 14 | 93.3% | |
| 🗿 | 1 | 6.67% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 10 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 15reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 22 March 2026 to 20 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
【7/23】新增 代理发展负责人 （标签：#市场 #运营 ） 工作地点： 迪拜（海外） 薪资福利：面议 岗位职责 * 负责公司代理体系的建设、管理及业务拓展； * 独立开发优质代理资源，建立并持续扩大代理网络； * 制定代理政策、合作模式、激励方案及管理机制； * 提升代理活跃度、代理产值及整体业务规模； * 负责代理团队的管理及业绩目标达成。 ⸻ 任职要求 必须具备 * 3年以上线上BC行业代理管理经验； * 有YB或其他国际知名平台代理体系相关工作经验； * 熟悉代理开发、代理运营、代理管理及分润模式； * 有独立拓展代理及管理代理团队的成功经验； * 具备优秀的商务拓展、谈判及资源整合能力。 优先考虑 * 有东南亚及周边国家市场经验； * 有成熟代理资源或行业人脉； * 熟悉Telegram、WhatsApp等渠道生态及代理合作模式。 ⸻ 关注重点（请准备） * 曾任职的平台及负责的市场； * 曾…
目前只有到岗迪拜的几个岗位相对急一点（AI全栈，架构，技术负责人，运营，业务），其他岗位相对不急迫，欢迎合适的朋友自荐推荐
AI Principal Architect（AI研发架构师） 我们正在推进研发组织AI化升级，寻找能够建设AI研发体系和大型业务架构的技术领导者。 岗位职责 负责核心架构设计与演进 制定AI研发体系规范 管理代码治理及技术标准 推动研发效率提升 负责关键业务系统架构决策 参与AI开发平台建设 任职要求 技术能力 10年以上研发经验 深度掌握Go生态 熟悉大型分布式系统架构 熟悉高并发、高可用设计 熟悉云原生体系 AI能力 深度使用AI开发工具 有AI驱动项目交付经验 熟悉Agent体系设计 熟悉RAG、MCP等相关技术 行业经验 优先考虑： BC行业 支付行业 金融科技行业 大型互联网平台经验 核心要求 能够通过AI放大团队整体产能，而不仅仅是个人开发效率。 工作地点：阿联酋迪拜 薪资：具备竞争力薪资福利，具体面议。
【6/15新增】 AI Native Full Stack Engineer- AI全栈开发工程师（Vue3 + Go） 我们正在构建AI驱动研发团队，希望寻找能够利用AI独立完成模块设计、开发、测试及上线交付的工程师。 岗位职责 负责业务模块全生命周期开发 基于Vue3与Go完成系统开发 利用AI工具完成需求分析、开发、测试及优化 配合业务负责人快速推动项目上线 持续优化AI开发工作流 任职要求 技术能力 5年以上开发经验 熟练掌握Vue3、TypeScript 熟练掌握Go开发 熟悉MySQL、Redis 熟悉RESTful API设计 AI能力（重点） 熟练使用Cursor、Claude Code等AI开发工具 能利用AI独立完成完整业务模块开发 有实际项目通过AI开发并上线经验 具备较强问题分析及代码Review能力 我们更关注 实际项目交付能力 AI开发能力 学习能力和执行力 而非单纯工作年限。 …
【6/15新增】 AI Native Technical Lead AI技术负责人（Go/Vue3） 我们正在建设AI Native研发团队。 开发工作已全面引入Cursor、Claude Code等AI工具，未来研发模式将以AI驱动开发为主，工程师核心职责是设计架构、管理AI开发流程、审核代码质量及推动项目交付。 岗位职责 负责核心业务系统架构设计与技术方案制定 利用AI工具完成复杂项目开发与交付 管理AI开发流程及Agent协作流程 审核AI生成代码并解决AI幻觉问题 负责关键模块技术攻关和代码质量治理 指导团队建立高效AI研发体系 任职要求 技术能力 8年以上研发经验 精通Go语言 熟悉Vue3及前后端分离架构 熟悉微服务、高并发、高可用系统设计 熟悉MySQL、Redis、Kafka等基础组件 有大型互联网系统架构经验 AI能力（重点） 深度使用Cursor、Claude Code、Copilot等工…
❤2
目前重点招聘运营经理，欢迎合适者自荐推荐，谢谢🙏
【4/24】新增 支付钱包风控运营 （序列：#运营， #风控） 📍 工作职责 1，交易风控策略制定与优化 ·负责平台支付钱包（充值/提现/转账等）的风控策略设计与持续优化 ·基于用户行为、交易特征建立风控规则（反洗钱、反欺诈、套利识别等） ·动态调整风控阈值，平衡风险与转化率 2，风险监控与异常处理 ·实时监控资金流动及异常交易行为（高频充值、异常提现、对敲等） ·搭建风险预警机制，并对高风险账户进行分级处理 ·负责风险事件的调查、复盘及闭环处理 3，反洗钱（AML）与合规支持 ·协助建立KYC/KYB、交易监测、可疑交易报告（STR）流程 ·跟进不同地区监管政策，确保支付及资金流符合当地合规要求 ·配合审计及监管检查 4，数据分析与模型支持 ·基于交易数据、用户行为数据进行分析，挖掘潜在风险模式 ·与数据/算法团队合作，推动风控模型（规则/评分卡/机器学习）建设 ·输出风控指标体系（如拒付率、欺诈率、通过率等） 4，跨部门…
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产品经理（加密钱包/支付/资金盘） （序列：#产品） 岗位职责 1. 钱包 & 资金体系 设计并搭建完整资金路径：用户 → 入金 → 钱包 → 交易/理财 → 提现 熟悉 USDT（TRC20 / ERC20）、归集、热冷钱包 优化到账速度、手续费、成功率 2. 入金 / 出金 对接并管理以下资源：四方支付（卡、码、U），OTC商户 / 承兑商，跑分 / 代收代付通道。解决核心问题（如成功率低，通道被封，到账延迟，资金安全） 3. 资金沉淀 & 变现 设计资金玩法：活期 / 定期 / 收益池 / 分红盘，质押借贷 / 杠杆，资金池滚动模型 提升核心指标：资金留存（不是DAU），复投率，ARPU 4. 风控与对抗 设计风控策略：限额、KYC分级，异常交易识别 理解并应对：通道风控，用户薅羊毛，黑产攻击 任职要求 1，三年以上相关工作经验（交易所钱包，四方支付/支付通道，OTC/承兑商体系，BC/社交盘/资金盘） 2，熟悉USDT…
开放一个3D动画设计师岗位，可远程，岗位要求见JD，符合者可投递，谢谢
新增SPINE动效设计师岗位一名，需求除了上述JD内容外，还需要做过直播间刷礼物的动效相关项目。符合者可投递简历，岗位可远程。谢谢 @hrzhaopin05
金融类产品经理正在招聘ing，需求是做过加密钱包以及三方四方支付的产品经验者，欢迎符合的朋友自荐推荐，谢谢
Showing the 12 most recent of 20 posts we hold for @ji_ys. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 851,352 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 3 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 August 2026 — this entry's latest reading, not the date you are reading this.
“集英社（海外求职招聘）” (@ji_ys), 1,598 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/ji_ys.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.