CakeResume 找人才
进阶搜寻
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Lead Engineer of CVD and Heat Treatment Process @PT Sumco Indonesia2018 ~ 现在
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Design Engineering
一個月內
ANDIKA NUR BIANTONO Design Engineering Continuous Improvement Engineering Bekasi, West Java, Indonesia I have 10 years of experience in a technical role as an engineer. I use some useful software (M.Office, Spotfire, JMP statistical software, CATIA, NX, Rhinoceros, AutoCAD) to do my work. My experience in designing automotive and shoe manufacturing (blow molding and Injection processes) as well as handling continuous improvement processes (mechanical, chemical and gas) for semiconductors and holds a Lean six sigma yellow belt. Work Experience Lead Engineer of CVD and Heat Treatment Process • PT Sumco Indonesia MarchPresent 1. Create documents
就职中
・
目前会考虑了解新的机会
全职 / 对远端工作有兴趣
10 到 15 年
Institut Teknologi Sepuluh Nopember Surabaya
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Shipbuilding
Lean Officer (with McKinsey & Company ) @ECOBANK PLC (Formerly Oceanic Bank Intl PLC) 2008 ~ 2009
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Lean and Six Sigma Practitioner
超過一年
abiodun adetula I help individuals and businesses to think and work smart, improve their processes & performance and create positive experiences with their Customers. I speak, teach, and facilitate brain storming sessions at conferences and retreats on Lean & Six Sigma, Customer Service, Supply Chain Management, Project Management & Soft Skills Lean and Six Sigma Practitioner City, NG [email protected] Work Experience ACCELTAGE CONSULTING, Chief Luminary Officer, Sep 2013 ~ Present ◼ Consultant for AIRTEL Nigeria and Ghana on Lean Six Sigma : In Ghana I Trained and Equipped the Cross Functional Teams CFTs made up of 45 employees with Lean
就职中
全职 / 对远端工作有兴趣
6 到 10 年
American Society for Quality
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Certified Six Sigma Black Belt, Certified Quality Process Analyst最轻量、快速的招募方案，数百家企业的选择
搜寻简历，主动联系求职者，提升招募效率。
- 浏览所有搜寻结果
- 每日可无限次数开启陌生对话
- 搜尋僅開放付費企業檢視的简历
- 检视使用者信箱 & 电话
搜寻技巧
1
Search a precise keyword combination
senior backend php
2
Use quotes to search for an exact phrase
"business development"
3
Use the minus sign to eliminate results containing certain words
UI designer -UX
职场能力评价定义
专业技能
该领域中具备哪些专业能力（例如熟悉 SEO 操作，且会使用相关工具）。
问题解决能力
能洞察、分析问题，并拟定方案有效解决问题。
变通能力
遇到突发事件能冷静应对，并随时调整专案、客户、技术的相对优先序。
沟通能力
有效传达个人想法，且愿意倾听他人意见并给予反馈。
时间管理能力
了解工作项目的优先顺序，有效运用时间，准时完成工作内容。
团队合作能力
具有向心力与团队责任感，愿意倾听他人意见并主动沟通协调。
领导力
专注于团队发展，有效引领团队采取行动，达成共同目标。
专业背景
目前状态
就职中
求职阶段
专业
数据科学家
产业
工作年资
1 到 2 年
管理经历
技能
语言能力
English
・
进阶
求职偏好
希望获得的职位
數據分析師、資料科學家
预期工作模式
全职
期望的工作地点
台灣台北
远端工作意愿
对远端工作有兴趣
接案服务
学历
学校
台灣大學
主修科系
統計
Education
National Taiwan University Taipei, Taiwan
Statistics, Master Degree GPA 3.94/4.3 (Rank 1th) 2016.09 - 2018.06
National Chengchi University Taipei, Taiwan
Statistics, Bachelor Degree 2013.09 - 2016.06
Work experience
Vanguard International Semiconductor Co. Hsinchu, Taiwan
algorithm engineer 2018.10 - 2020.3- Designed an anomaly detection model for monitoring the health of semiconductor manufacturing equipments.
- Built and combined three models, Moving Average Model, AutoEncoder and Multi-Scale Convolutional Recurrent Encoder Decoder (MSCRED), to improve higher accuracy.
- Used SAS JMP to perform data preprocessing and python with Tensorflow framework to build the model.
- Saved every module engineer 1 hour per day.
- Designed a wafer defect detection and classification model on photos provided from Automated Optical Inspection (AOI).
- Used object detection model, Faster R-CNN, with Tensorflow framework.
- Achieved 85% accuracy, and 90% recall rate.
- Design Automatic Virtual Metrology to update the parameter settings of equipments in real time.
- Used Dense Neural Network with Keras framework.
- Equipment parameters were estimated and updated
Publication
Semiparametric regression analysis of current status data under sequential monitoring
- Developed a semiparametric estimation method for regression analysis based on the sequential monitoring data.
- Introduced the additive hazards regression on sequential data to utilize the comprehensive monitoring information.
- Proposed a two-stage estimation procedure by pooling the sequence of the current status at monitoring times to estimate the regression coefficients in the semiparametric additive hazard model.
- Used R to conduct extensive simulation studies with various censoring rates and monitoring frequencies to investigate the performance. The result indicated that this model has a good performance, which has bias less than 0.01 and is close to the right censored data result.
Award
The 5th E.SUN commercial bank SAS competition: excellent work
Big Data Data Scientist Competition Text Analysis and Digital Marketing Competition
- Lead a team of four, including one member majoring marketing, to develop feasible marketing strategy candidates, and then designed further analyzing procedures and models respectively.
- Implemented descriptive statistics with SAS Text Miner to analyze forum texts and search logs from the official site of E.SUN, to identify different costumer groups and their corresponding consumption propensities.
- Implemented a Decision Tree model, with SAS, SAS VA and SAS Viya, to predict customers’ purchasing power based on customer profile and their credit card history, which achieved 86% accuracy.
- Based the analysis and model, we selected the most important variables and decided our major target group, and proposed our final marketing strategy.
Skills
- python, R,
- SAS, SAS JMP
- pytorch, tensorflow, keras
selected courses
- Mathematical statistics (2016 Fall) A
- Applied Bayesian statistical method (2016 Fall) A-
- Biostatistics research methods (2016 Fall) A
- Principles and applications of computational biology (2017 Spring) A
- Machine learning (2017 Spring) A-
- Advanced Medical Statistics Method 1 (2017 Fall) A+
- Survival analysis (2018 Spring) A+
- Category analysis (2018 Spring) A+
Education
National Taiwan University Taipei, Taiwan
Statistics, Master Degree GPA 3.94/4.3 (Rank 1th) 2016.09 - 2018.06
National Chengchi University Taipei, Taiwan
Statistics, Bachelor Degree 2013.09 - 2016.06
Work experience
Vanguard International Semiconductor Co. Hsinchu, Taiwan
algorithm engineer 2018.10 - 2020.3- Designed an anomaly detection model for monitoring the health of semiconductor manufacturing equipments.
- Built and combined three models, Moving Average Model, AutoEncoder and Multi-Scale Convolutional Recurrent Encoder Decoder (MSCRED), to improve higher accuracy.
- Used SAS JMP to perform data preprocessing and python with Tensorflow framework to build the model.
- Saved every module engineer 1 hour per day.
- Designed a wafer defect detection and classification model on photos provided from Automated Optical Inspection (AOI).
- Used object detection model, Faster R-CNN, with Tensorflow framework.
- Achieved 85% accuracy, and 90% recall rate.
- Design Automatic Virtual Metrology to update the parameter settings of equipments in real time.
- Used Dense Neural Network with Keras framework.
- Equipment parameters were estimated and updated
Publication
Semiparametric regression analysis of current status data under sequential monitoring
- Developed a semiparametric estimation method for regression analysis based on the sequential monitoring data.
- Introduced the additive hazards regression on sequential data to utilize the comprehensive monitoring information.
- Proposed a two-stage estimation procedure by pooling the sequence of the current status at monitoring times to estimate the regression coefficients in the semiparametric additive hazard model.
- Used R to conduct extensive simulation studies with various censoring rates and monitoring frequencies to investigate the performance. The result indicated that this model has a good performance, which has bias less than 0.01 and is close to the right censored data result.
Award
The 5th E.SUN commercial bank SAS competition: excellent work
Big Data Data Scientist Competition Text Analysis and Digital Marketing Competition
- Lead a team of four, including one member majoring marketing, to develop feasible marketing strategy candidates, and then designed further analyzing procedures and models respectively.
- Implemented descriptive statistics with SAS Text Miner to analyze forum texts and search logs from the official site of E.SUN, to identify different costumer groups and their corresponding consumption propensities.
- Implemented a Decision Tree model, with SAS, SAS VA and SAS Viya, to predict customers’ purchasing power based on customer profile and their credit card history, which achieved 86% accuracy.
- Based the analysis and model, we selected the most important variables and decided our major target group, and proposed our final marketing strategy.
Skills
- python, R,
- SAS, SAS JMP
- pytorch, tensorflow, keras
selected courses
- Mathematical statistics (2016 Fall) A
- Applied Bayesian statistical method (2016 Fall) A-
- Biostatistics research methods (2016 Fall) A
- Principles and applications of computational biology (2017 Spring) A
- Machine learning (2017 Spring) A-
- Advanced Medical Statistics Method 1 (2017 Fall) A+
- Survival analysis (2018 Spring) A+
- Category analysis (2018 Spring) A+