Data Analyst / User Growth / BI

LEYA YANG

Data Analyst & User Growth Specialist, driving business value with data insights.

数据分析与用户增长专家，以深度数据洞察驱动商业增长与转化。

Master of Data Analysis and Finance from the University of Sydney, and Bachelor of Environmental Engineering from the University of Melbourne. Over 2 years of experience in data analytics, user profiling, conversion funnel optimization, A/B testing, and business predictive modeling. Proven track record of boosting revenue (¥35.6k+ monthly contribution) and optimizing ROI (up to 180%).

悉尼大学数据分析与金融硕士，墨尔本大学环境工程本科。拥有 2 年以上数据分析与用户增长经验，擅长用户画像、转化漏斗剖析、A/B 测试和业务预测建模。曾成功主导会员体系重构实现单月增收超 35.6 万元，并优化广告投放 ROI 达 180%。

¥35.6w+ Monthly revenue contribution 单月核心产品营收贡献

180% Ad placement ROI target achieved 广告投放 ROI 优化成果

0.017 RMSE in Box Office Model 票房预测回归模型误差 (RMSE)

View Experience 查看经历 Download Resume 下载简历 (PDF)

Experience & Education

经历与教育背景

Work Experience

工作经历

2024.02 — 2025.09 Shanghai Jiguo Info Tech 上海即果信息技术有限公司

Data Analyst

数据分析师

Reconstructed the membership value tiering using LTV and RFM models, introducing tiered subscription cycles ("3/30/90 days") that converted single-purchase users to subscribers and generated ¥35.6k+ monthly revenue (13% of daily total). Led review of female user matching privileges, detected 33% drop in pay rate from capping free matches, and rolled back strategy to save high-value users. Blocked inefficient redirection features by estimating ¥2,500 daily revenue loss. Optimized "location card" visibility based on funnel analysis, lifting pay rate from 1.2% to 2% and boosting weekly daily revenue by 100%+.

商业化会员增长：通过 RFM 和 LTV 模型进行用户价值分层，设计并落地“3日/30日/90日”分层会员体系，单月贡献营收超 35.6 万元（占日均总营收 13%）。策略风控与 A/B 测试：主导“女性用户匹配权益”A/B测试复盘，漏斗分析定位免费次数限制导致付费率环比下跌 33% 风险并实施策略回滚；测算流量分发变现效率，规避日均 ¥2,500 收入折损。精细化权益运营：对比不同 SKU 转化漏斗，优化“位置卡”在匹配页的曝光，使付费率从 1.2% 提升至 2%，带动该功能周均日流水环比增长超 100%。

2023.04 — 2023.12 Hangzhou Make a Friend Net Tech 杭州美个朋友网络科技公司

Data Analyst (Overseas User Growth)

数据分析师（海外用户增长）

Processed 30k+ user behavior data using Python to build comprehensive user profiles and formulated targeted user acquisition plans. Set up ad conversion funnel tracking, monitored retention and repurchase, designed and evaluated A/B tests for ad creatives, successfully improving ROI to 180%. Built LSTM/ARIMA forecasting models for ROI trends to set Q2/Q3 KPI benchmarks. Created automated Tableau reports and workflow maps to cut decision cycle to under 24 hours.

用户画像与策略洞察：使用 Python 清洗 3万+ 用户数据，从地理位置、购买偏好等维度构建画像，产出针对性的投放策略。投放效果优化：搭建投放漏斗模型全链路监控，设计 A/B 实验测试广告素材和文案，将投放 ROI 提升至 180%。趋势预测与可视化：基于 LSTM/ARIMA 预测 ROI 趋势以辅助 KPI 制定。利用 Tableau 与 Xmind 建立自动报表，将决策响应缩短至 24 小时内。

Education

教育背景

2021.02 — 2023.02 The University of Sydney 悉尼大学 (QS19)

Master of Data Analysis and Finance

数据分析与金融硕士

Core Courses: Statistical Data Mining, Machine Learning, Predictive Analysis, International Business Finance, Corporate Finance, Financial Theory, Derivatives, Data Visualization.

主要课程：统计与数据挖掘，机器学习，预测分析，国际商业金融，企业金融，金融理论，衍生品，数据可视化。

2018.02 — 2021.02 The University of Melbourne 墨尔本大学 (QS14)

Bachelor of Environmental Engineering

环境工程本科

Core Courses: Data Analysis, Engineering Risk Analysis, Fluid Mechanics, Environmental Management.

主要课程：数据分析，工程风险分析，流体力学，环境治理。

Selected Analytics Cases

精选项目案例

Shanghai Jiguo · Growth Strategy 上海即果 · 用户增长 Membership Growth & Commercialization Re-structuring 商业化会员增长与权益体系重构

Addressed single-purchase dependency by establishing user value layer models (LTV, RFM) on historical payment details. Designed and shipped "3-day/30-day/90-day" subscription structures, shifting transactional users to recurring billing.

针对营收过分依赖单次消耗道具的痛点，提取用户历史充值行为，构建 LTV 与 RFM 模型进行价值分层；设计并落地“3日/30日/90日”分层会员体系，将高价值用户转化为长期订阅用户。

¥35.6w+ Monthly revenue growth contribution ¥35.6w+ 单月核心产品增收 +¥0.3 Average ARPU increment +¥0.3 整体 ARPU 提升 13% Constant share of total daily revenue 13% 稳定占日营收比重

Shanghai Jiguo · A/B Testing 上海即果 · 策略风控 Funnel Analysis & Matching Rules Wind Control 策略风控与 A/B 测试复盘止损

Analyzed female users' conversion funnels. Detected that match limitation caused high-value female pay rate to drop by 33%; successfully initiated strategy rollbacks. Evaluated redirection features and blocked inefficient traffic diversion, saving daily revenue.

主导女性匹配权益调整 A/B 测试复盘。漏斗分析发现免费限制导致女性付费率下跌 33%，启动预警和回滚；测算流量分发变现效率，规避日均 ¥2,500 流量价值浪费。

-33% → Restored Female matching pay rate -33% → 恢复 挽回付费率下跌 ¥2,500/day Revenue loss prevented ¥2,500/日 避免分流带来的折损

Screen Australia · Forecasting Screen Australia · 机器学习 Machine Learning Box Office Prediction Model 跨度 22 年电影票房高精度预测项目

Led the cooperation project with Screen Australia. Cleaned 22-year movie records and extracted critical features through exploratory data analysis (EDA). Built Random Forest and Gradient Boosting models, using Lasso/Ridge regularization to ensure generalization.

主导与 Screen Australia 合作项目，清洗处理跨度 22 年的 10万+ 票房数据点；提取 40 维核心特征，构建随机森林与梯度提升模型，并解决过拟合风险。

100k+ Cleaned box office data points 100k+ 数据点特征工程 0.017 Predictive model RMSE achieved 0.017 高精度 RMSE 预测结果

Capabilities & Core Skills

专业核心技能

Data Science & Programming

数据科学与编程

Python, SQL, R, Pandas, NumPy, Matplotlib, exploratory data analysis (EDA), database query extraction, and data cleaning pipelines.

Python, SQL, R, Pandas, NumPy, Matplotlib, 探索性数据分析 (EDA)、数据库检索、以及高效的数据清洗流程。

Growth Strategy & Analytics

增长策略与分析方法

A/B Testing, funnel analysis (Funnel Analysis), RFM segmentation models, LTV estimation, cohort analytics, retention, and churn analysis.

A/B 测试实验设计、转化漏斗分析 (Funnel Analysis)、RFM 用户分层、LTV 模型、同期群与留存分析。

Machine Learning & Forecasting

机器学习与商业预测

Regression modeling, ensemble trees (Random Forest, Gradient Boosting), and time-series modeling (LSTM, ARIMA) for ROI & metric forecasting.

回归建模、决策树集成算法（随机森林、梯度提升）、基于 LSTM / ARIMA 的时序预测（用于指标与 ROI 变化趋势预测）。

BI Tools & Visualizations

商业智能与可视化

Tableau report design, Zeppelin analytics, MongoDB query, MS Office, Xmind data flow structuring, and automated report administration.

Tableau 仪表盘搭建、Zeppelin 可视化分析、MongoDB、MS Office，以及基于 Xmind 的业务数据流标准化管理。

Connect

联系与合作

Interested in growth analytics, data modeling, or business intelligence? Let's connect.

对数据分析、用户增长、商业化变现等话题感兴趣？欢迎与我联系。

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