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4-6 năm
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Lead Engineer of CVD and Heat Treatment Process @PT Sumco Indonesia2018 ~ Hiện tại
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Design Engineering
Trong vòng một tháng
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
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Full-time / Quan tâm đến làm việc từ xa
10-15 năm
Institut Teknologi Sepuluh Nopember Surabaya
・
Shipbuilding
Lean Officer (with McKinsey & Company ) @ECOBANK PLC (Formerly Oceanic Bank Intl PLC) 2008 ~ 2009
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Lean and Six Sigma Practitioner
Hơn một năm
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
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Full-time / Quan tâm đến làm việc từ xa
6-10 năm
American Society for Quality
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Certified Six Sigma Black Belt, Certified Quality Process AnalystKế hoạch tuyển dụng đơn giản và hiệu quả nhất
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Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
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Tiến trình tìm việc
Professions
Data Scientist
Fields of Employment
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1-2 năm
Management
Kỹ năng
Ngôn ngữ
English
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Vị trí
數據分析師、資料科學家
Loại hình công việc
Full-time
Địa điểm
台灣台北
Làm việc từ xa
Quan tâm đến làm việc từ xa
Freelance
Học vấn
Trường học
台灣大學
Chuyên ngành
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+