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De 4 a 6 años
6-10 años
10-15 años
Más de 15 años
Past
Assistant Accounting Finance Manager @Vacation Homes 3652019 ~ Presente
・
Administration Staff and Customer Service
En un mes
John Michael Sorbito RN Versatile and experienced professional with a proven track record of success in customer service, sales, and education. Expertise in building rapport, resolving issues, and achieving sales targets. Passionate about helping others and delivering exceptional results. Bacolod, Negros Occidental, Philippines Work Experience Assistant Accounts and Finance Manager • Vacation Homes 365 JanuaryFebruary 2024 •Manage 60 properties listed through Airbnb, booking.com and VRBO as well. • Manage property listings and pricing include rate adjustment and resolution managements. •Developed and maintained a system for tracking accounts receivable and accounts payable •Handles all Invoicing responsibilities
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
6-10 años
Carlos Hilado Memorial State University
・
Education
Past
Peformance & Mental Coach @Onic Esports2019 ~ 2021
・
Marketing
En un mes
. Collaborate with the coaching staff to create a cohesive training plan that aligns with the team's overall goals and objectives. 5. Provide feedback and constructive criticism to players in a supportive manner to help them reach their full potential. 6. Analyze gameplay footage and statistics to identify areas for improvement and track progress over time. 7. Assist players in managing performance-related stress and pressure, and provide mental coaching strategies to enhance their resilience and mental toughness. 8. Stay updated on the latest trends and strategies in the esports industry
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
Universitas Katolik Atmajaya Jakarta
・
Akuntansi
Project Manager @明基電通2022 ~ Presente
・
Service Manager or Project Manager or Supply Chain Manager or Purchaser
En un mes
Service Quality Project Management. Service Expense Budget Planning, Cost Control, and Regular Review Adjustments. Government Project Service Cost Calculation. Cross-department/Business Unit/Subsidiary Communication and Resource Coordination. Project Problem Solving and Tracking. Project Progress Planning and Management. Expense Audit and Review of Missing Components for Improvement. Financial Report Compilation and Analysis. Service Performance Indicator Statistics and Analysis. Compilation of Annual Budget Data from Various Business Units. Company Annual Budget Meeting Presentation. Salesforce System Platform Management and Maintenance. Achievements: 1. Global C...
Empleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
Yuan-Ze University
・
製造工程與經營管理系
Past
Software Developer @PERBASI2023 ~ Presente
・
Senior Backend Engineer
En un mes
Zikri Alghifahri - Date of Birth 15th JanuaryStarting Carrier as Programmer in 2013 Indonesia Work Experience MarchPresent Software Developer PERBASI Working within Basketball Athletes to gather Data & statistics. Now sports and technology cannot be separated from each other. Therefore, I designed a system that can record all athlete activities and display them into a data set that can be read and studied in the future. Machine learning is the tool I use to achieve this. Currently, Tensorflow is one of the frameworks that I use to support my needs. NovemberPresent Software Developer Dinas Perpustakaan & Arsip Pesawaran
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
6-10 años
Universitas Teknokrat Indonesia
・
Computer Science
QA automation engineer / Software development engineer in test
En un mes
Good at test planning, defined test strategy, implementing test plan and test cases also build up the test environment. Issue feedback and reporting, bug tracking and data analyzing. Program: Python, My SQL, Google Data Studio, ADB commands Education Fu Jen Catholic University~Master of Science i n Applied Statistics Fu Jen Catholic University~Bachelor of Statistics and Information Science Work Experience Google-PTE (Pixel Testing Engineer Team/01~2023/03) NOVMAR 2023 Pixel Acoustics Automation Test Development Acoustics automation and benchmark testing for PixelDesigned the test automation for measuring the speaker quality to enhance the test
Desempleado
・
Listo para la entrevista
A tiempo completo / No está interesado en trabajar a distancia
6-10 años
Past
Team Leader @TaskUs 美商泰優股份有限公司台灣分公司2018 ~ Presente
・
Team Leader
En el plazo de dos meses
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
淡江大學 Tamkang University
・
法文Past
行銷企劃專員 (約聘實習) @新加坡商邁盛絡國際企業有限公司 Maxonrow2019 ~ 2019
・
主管特別助理、財務分析／財務人員、行銷企劃人員、活動企劃人員、網站行銷企劃
En un mes
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
10-15 años
國立政治大學
・
MarketingEmpleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
6-10 años
National Sun Yat-Sen University
・
網路資訊
Director of Product Engineering @SV TCL2017 ~ Presente
・
管理職
En un mes
Blair Yu Director of Product Engineering at SV TCL Multi-site and Multi-culture communication and team work experience (countries includes Autria, China, Czech, German, Neitherland, Mexico, USA, Switzerland) Problem solving with solid logic thinking Large team (30+ team members) leading and management People and team development Risk assessment with mitigation plan Team coaching and motivation Specialties: SPC, Statistic Process Control Skill and knowledge FMEA analysis and action plan Hsinchu, Hsinchu City, [email protected] https://www.linkedin.com/in/bert-blair-yu-pmp-89334a20/ 工作經歷 一
Empleado
・
Listo para la entrevista
A tiempo completo / No está interesado en trabajar a distancia
Más de 15 años
NTOU (Unofficial)
・
Material Engineering
Past
Lead Data Scientist / Senior Data Scientist @Vinnovation Network 維諾森資訊科技2022 ~ 2023
・
資料科學家、資料科學工程師、機器學習工程師
En un mes
Shih-Wen Tsou - With more than 5 years of experience in Data Analysis, Machine Learning and Deep Learning, familiar with Modeling, Data Analysis, Image Processing, Machine Learning, and Deep Learning. Taipei City, Taiwan WORK EXPERIENCE Lead Data Scientist / Full Stack Data Scientist, Vinnovation Network, Taipei, Taiwan Data Engineering / Data Analysis Spearheaded the development of a fully automated data integration pipeline that aggregated diverse data sets into a S3 Data Lake. Successfully integrated a range of data sources, including real-time data feeds from AWS Redshift and DocumentDB, as well as batch processes to import traditional CSV
Desempleado
・
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
台灣大學
・
大氣科學所El plan de reclutamiento más ligero y eficaz
Busque currículums y tome la iniciativa de ponerse en contacto con los solicitantes de empleo para lograr una mayor eficacia en la contratación. La elección de cientos de empresas.
- Examinar todos los resultados de la búsqueda
- Acceso ilimitado para iniciar nuevas conversaciones
- currículos accesibles sólo para empresas de pago
- Ver dirección de correo electrónico y números de teléfono de los usuarios
Consejos de búsqueda
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
Sólo los currículums públicos están disponibles con el plan gratuito.
Actualiza a un plan avanzado para ver todos los resultados de la búsqueda incluyendo decenas de miles de currículums exclusivos en CakeResume.
Definition of Reputation Credits
Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
Communication
Ability to convey information effectively and is willing to give and receive feedback.
Time Management
Ability to prioritize tasks based on importance; and have them completed within the assigned timeline.
Teamwork
Ability to work cooperatively, communicate effectively, and anticipate each other's demands, resulting in coordinated collective action.
Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Professional Background
Situación actual
Empleado
Progreso en la búsqueda de empleo
Professions
Data Scientist, Machine Learning Engineer
Fields of Employment
Banca, Inteligencia Artificial / Aprendizaje Automático, AdTech / MarTech
Experiencia laboral
De 4 a 6 años
Management
Ninguno
Habilidades
Idiomas
English
・
Fluido
Job search preferences
Posición
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Tipo de trabajo
A tiempo completo
Ubicación
台灣台北, 台灣新北市
A distancia
Interesado en trabajar a distancia
Freelance
Sí, soy un autónomo amateur.
Educación
Escuela
政治大學
Mayor
統計
Education
National Chenchi University, MS, Statistics, 2015 – 2017
- GPA : 3.84 / 4.0
- Master Thesis: Entropy Based Feature Selection, Professor Pei-Ting, Chou
- Objective: Build a similarity matrix based on Mutual Entropy under Hierarchical Clustering. Afterwards, select clustered features as the final selection.
- Compare the model with other feature selection methods like RF, Lasso, F-score.
National Chen-Kung University, BS, Mathematics, 2011 – 2015
Skills
Programing
- Python
- Scala
- R
- MSSQL
Data-related Tools
- Tensorflow (Keras)
- PyTorch
- Spark
- Docker
- Scikit-Learn
- Pandas
Cloud Platform
- AWS
- GCP
Language
- English: TOEFL 98 / 120
Work Experience
CTBC Bank, Model Development Department, Data Scientist
2021.12 – present
- About the department:
- Responsible for developing models related to bank recommendations and risks, including projects such as coupon recommendations, account opening marketing lists, and fraud detection.
- Job responsibilities:
- Throughout the entire project lifecycle, my primary responsibilities included model design, model training, end-to-end process development, feature design, performance tracking, and method research.
Fraud Alert Project
- Objective:
- Predicting potential fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm.
- Responsibilities/Achievements:
- Development and deployment of credit card and financial features.
- Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists.
- Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness.
Coupon Recommendation
- Objective:
- Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates.
- Responsibilities/Achievements:
- Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a 14% increase in click-through rate and a 74% increase in redemption rate.
- Created performance tracking reports to monitor online model performance and provide insights to Business Units.
Financial Product Recommendations
- Objective:
- Tailored financial product recommendations for mobile banking users to enhance click-through rates without compromising conversion rates.
- Responsibilities/Achievements:
- Applied multi-task learning to jointly learn click-through and conversion behaviors, fine-tuned model architecture, achieving a 90% outperformance against competitor models in online testing.
Marketing List for Digital Savings Accounts
- Objective:
- Optimized conversion rates for marketing lists related to digital savings accounts
- Responsibilities/Achievements:
- successfully raising conversion rates from 0.23% to 1.16%
Work Experience
CLICKFORCE, Data Engineer Supervisor, 2020.1 – 2021.11
- About the company:
- As a top domestic digital advertisement company, CLICKFORCE cooperates with over 900 web media and over 400 mobile media to build a huge advertising environment. CLICKFORCE considers data-driven solution as the core concept of the company, and dedicates to help advertisers to achieve their commercial goals.
- At 2020, CLICKFORCE won 2 awards at Agency & Advertiser of the Year.
- Successfully acquire the exclusive advertising agency qualification for Tokyo 2020 Olympics in Taiwan.
- Job responsibilities:
- Optimize ad performance from all aspects, including the system, target audience tags, etc.
- Do researches for new ML model (recommender model, NLP model) or architecture which is suitable for our system.
- Develop data-related products or projects.
- Analyze data to help improve our system or inspect whether the demands from business side is doable.
Real-time AD Recommender System
- Objective:
- Building a real-time ad recommender system to upgrade our ad server and get better performance.
- Responsibilities:
- Figure out what kind of recommender system components that is suitable for our ad system.
- Build a tower-like and feature-cross model refer to other famous recommender system model.
- Responsible for system engineering, which includes data preprocessing, embedding generates, memory cache, cold start, model API, etc.
Interest Tags
- Objective:
- Build interest tags for ads to help ad optimizers choose their target audience.
- Responsibilities:
- Create the features from what articles they saw, what website they viewed, and what ads they interacted.
- Deal with 20 million rows data and 120 million inference samples.
- Build ML model to predict each user's behavior on certain ads.
- Using Spark through AWS EMR to accelerate the speed of producing tags.
- Achievements:
- Raise CTR performance up to 200-300% of the original tags depends on different tags, and gain more impression while maintain better performance.
- After accomplishing this project, we terminated the cost on purchasing interest tags from other company, and successfully turned the original cost into revenue by providing profitable data.
First Party Cookie Mapping
- Objective:
- Deal with the Google 3rd party Cookie issue, figure out a method to map numerous 1st party Cookies to a user.
- Responsibility:
- Transform this problem into a ML mission. Design the label of the data, figure out what feature we can get or produce and whether the feature is useful for the goal.
- Apply XGboost on this mission.
- Build a small test to prove this method works.
- Achievement:
- 70% of precision.
- One of the solution of our company while the cancelation of 3rd party Cookie happen.
Invoice Data Application
- Objective:
- Develop invoice data application.
- Responsibility:
- Responsible for fine-tuning BERT to predict category for each product.
- Produce invoice data report to brands or business unit. It demonstrates the sales volume across different channel, what kind of products are frequently bought together, and also shows comparison of target brand to the other brands.
- Achievements:
- Produce an invoice data report product.
- Produce invoice tags for ad system.
Other Experience
E.Sun AI 2020 Summer Competition, 2020.7 – 2020.8
- Objective:
- Extract names of money laundering suspects from an article.
- Responsibilities:
- Crawl the articles from different media, and parse them by using Selenium, Requests, and Beautiful Soup.
- Construct 2-step model: First, identify whether the article is related to money laundering. Second, extract the suspects' names.
- Build model serving API by Tensorflow Serving.
- Build REST API for preprocessing request data and return the prediction.
- Achievement:
- 23rd place among 409 teams.
Youtube Data-Driven Marketing System, Institute for Information Industry, 2019.8 – 2019.11
- Objectives:
- Use the title and the description of videos to automatically classify videos.
- Use the title and the description of videos to identify whether a video is sponsored.
- Give suggestions for Youtubers or companies who desire to sponsor in a video based on data analysis.
- Responsibilities:
- Apply Google API and write Python functions to get structured raw data.
- Train word vectors using Gensim based on Wiki's open data.
- Use the frequency of each sentence as a criteria to eliminate useless words.
- Tune LSTM, Conv1D, BERT on the NLP mission.
- Use EDA methods to see the insights of the data under different classes and different sponsored status.
- Achievement:
- 71% accuracy in classifying video’s type.
- 89% accuracy in detecting sponsored content.
E.Sun Real Estate Price Prediction Competition, 2019.7 – 2019.8
- Objective:
- Use the real estate training data to build a model and predict the real estate price within 10% residual.
- Responsibilities:
- Apply XGBoost, LGBM and other ML models to train the model.
- Collect the outputs as new features from each ML model and add them into the original data set to enhance the performance of the final model.
- Achievement:
- 150th place out of 1200 teams.
KKTV Data Game，2017.5 – 2017.6
- Objective:
- Predict the next video a user watch in the next time interval.
- Responsibilities:
- Extract different features from raw data, such as the latest video, the video which got the longest viewing time, the video which got the largest number of viewing.
- Use the user viewing data to construct a similarity matrix of each video as additional features.
- Achievement:
- 10th place out of 50 teams.
MRT Open Data Competition, 2017.4 – 2017.5
- Objective:
- Study the changes of passenger volume of MRT by surrounding geometric data.
- Responsibilities:
- Apply bisection method to build the edges between MRT stations.
- Combine other geometric data based on these borders.
- Use Lasso feature selection method to explore the importance of each feature.
- Add noises into features to check the features are not randomly selected.
- Achievement:
- Certificate of Honorable Mention.
Education
National Chenchi University, MS, Statistics, 2015 – 2017
- GPA : 3.84 / 4.0
- Master Thesis: Entropy Based Feature Selection, Professor Pei-Ting, Chou
- Objective: Build a similarity matrix based on Mutual Entropy under Hierarchical Clustering. Afterwards, select clustered features as the final selection.
- Compare the model with other feature selection methods like RF, Lasso, F-score.
National Chen-Kung University, BS, Mathematics, 2011 – 2015
Skills
Programing
- Python
- Scala
- R
- MSSQL
Data-related Tools
- Tensorflow (Keras)
- PyTorch
- Spark
- Docker
- Scikit-Learn
- Pandas
Cloud Platform
- AWS
- GCP
Language
- English: TOEFL 98 / 120
Work Experience
CTBC Bank, Model Development Department, Data Scientist
2021.12 – present
- About the department:
- Responsible for developing models related to bank recommendations and risks, including projects such as coupon recommendations, account opening marketing lists, and fraud detection.
- Job responsibilities:
- Throughout the entire project lifecycle, my primary responsibilities included model design, model training, end-to-end process development, feature design, performance tracking, and method research.
Fraud Alert Project
- Objective:
- Predicting potential fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm.
- Responsibilities/Achievements:
- Development and deployment of credit card and financial features.
- Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists.
- Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness.
Coupon Recommendation
- Objective:
- Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates.
- Responsibilities/Achievements:
- Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a 14% increase in click-through rate and a 74% increase in redemption rate.
- Created performance tracking reports to monitor online model performance and provide insights to Business Units.
Financial Product Recommendations
- Objective:
- Tailored financial product recommendations for mobile banking users to enhance click-through rates without compromising conversion rates.
- Responsibilities/Achievements:
- Applied multi-task learning to jointly learn click-through and conversion behaviors, fine-tuned model architecture, achieving a 90% outperformance against competitor models in online testing.
Marketing List for Digital Savings Accounts
- Objective:
- Optimized conversion rates for marketing lists related to digital savings accounts
- Responsibilities/Achievements:
- successfully raising conversion rates from 0.23% to 1.16%
Work Experience
CLICKFORCE, Data Engineer Supervisor, 2020.1 – 2021.11
- About the company:
- As a top domestic digital advertisement company, CLICKFORCE cooperates with over 900 web media and over 400 mobile media to build a huge advertising environment. CLICKFORCE considers data-driven solution as the core concept of the company, and dedicates to help advertisers to achieve their commercial goals.
- At 2020, CLICKFORCE won 2 awards at Agency & Advertiser of the Year.
- Successfully acquire the exclusive advertising agency qualification for Tokyo 2020 Olympics in Taiwan.
- Job responsibilities:
- Optimize ad performance from all aspects, including the system, target audience tags, etc.
- Do researches for new ML model (recommender model, NLP model) or architecture which is suitable for our system.
- Develop data-related products or projects.
- Analyze data to help improve our system or inspect whether the demands from business side is doable.
Real-time AD Recommender System
- Objective:
- Building a real-time ad recommender system to upgrade our ad server and get better performance.
- Responsibilities:
- Figure out what kind of recommender system components that is suitable for our ad system.
- Build a tower-like and feature-cross model refer to other famous recommender system model.
- Responsible for system engineering, which includes data preprocessing, embedding generates, memory cache, cold start, model API, etc.
Interest Tags
- Objective:
- Build interest tags for ads to help ad optimizers choose their target audience.
- Responsibilities:
- Create the features from what articles they saw, what website they viewed, and what ads they interacted.
- Deal with 20 million rows data and 120 million inference samples.
- Build ML model to predict each user's behavior on certain ads.
- Using Spark through AWS EMR to accelerate the speed of producing tags.
- Achievements:
- Raise CTR performance up to 200-300% of the original tags depends on different tags, and gain more impression while maintain better performance.
- After accomplishing this project, we terminated the cost on purchasing interest tags from other company, and successfully turned the original cost into revenue by providing profitable data.
First Party Cookie Mapping
- Objective:
- Deal with the Google 3rd party Cookie issue, figure out a method to map numerous 1st party Cookies to a user.
- Responsibility:
- Transform this problem into a ML mission. Design the label of the data, figure out what feature we can get or produce and whether the feature is useful for the goal.
- Apply XGboost on this mission.
- Build a small test to prove this method works.
- Achievement:
- 70% of precision.
- One of the solution of our company while the cancelation of 3rd party Cookie happen.
Invoice Data Application
- Objective:
- Develop invoice data application.
- Responsibility:
- Responsible for fine-tuning BERT to predict category for each product.
- Produce invoice data report to brands or business unit. It demonstrates the sales volume across different channel, what kind of products are frequently bought together, and also shows comparison of target brand to the other brands.
- Achievements:
- Produce an invoice data report product.
- Produce invoice tags for ad system.
Other Experience
E.Sun AI 2020 Summer Competition, 2020.7 – 2020.8
- Objective:
- Extract names of money laundering suspects from an article.
- Responsibilities:
- Crawl the articles from different media, and parse them by using Selenium, Requests, and Beautiful Soup.
- Construct 2-step model: First, identify whether the article is related to money laundering. Second, extract the suspects' names.
- Build model serving API by Tensorflow Serving.
- Build REST API for preprocessing request data and return the prediction.
- Achievement:
- 23rd place among 409 teams.
Youtube Data-Driven Marketing System, Institute for Information Industry, 2019.8 – 2019.11
- Objectives:
- Use the title and the description of videos to automatically classify videos.
- Use the title and the description of videos to identify whether a video is sponsored.
- Give suggestions for Youtubers or companies who desire to sponsor in a video based on data analysis.
- Responsibilities:
- Apply Google API and write Python functions to get structured raw data.
- Train word vectors using Gensim based on Wiki's open data.
- Use the frequency of each sentence as a criteria to eliminate useless words.
- Tune LSTM, Conv1D, BERT on the NLP mission.
- Use EDA methods to see the insights of the data under different classes and different sponsored status.
- Achievement:
- 71% accuracy in classifying video’s type.
- 89% accuracy in detecting sponsored content.
E.Sun Real Estate Price Prediction Competition, 2019.7 – 2019.8
- Objective:
- Use the real estate training data to build a model and predict the real estate price within 10% residual.
- Responsibilities:
- Apply XGBoost, LGBM and other ML models to train the model.
- Collect the outputs as new features from each ML model and add them into the original data set to enhance the performance of the final model.
- Achievement:
- 150th place out of 1200 teams.
KKTV Data Game，2017.5 – 2017.6
- Objective:
- Predict the next video a user watch in the next time interval.
- Responsibilities:
- Extract different features from raw data, such as the latest video, the video which got the longest viewing time, the video which got the largest number of viewing.
- Use the user viewing data to construct a similarity matrix of each video as additional features.
- Achievement:
- 10th place out of 50 teams.
MRT Open Data Competition, 2017.4 – 2017.5
- Objective:
- Study the changes of passenger volume of MRT by surrounding geometric data.
- Responsibilities:
- Apply bisection method to build the edges between MRT stations.
- Combine other geometric data based on these borders.
- Use Lasso feature selection method to explore the importance of each feature.
- Add noises into features to check the features are not randomly selected.
- Achievement:
- Certificate of Honorable Mention.