Senior Data Scientist
Resume:
Tien (Minh) Nguyen
Data Scientist
About Me
Professional Experience
With 4 years of experience as a Data Scientist, I've worked with a diverse range of clients on Upwork and actively participated in various Data Science challenges. I bring a dedicated and detail- oriented approach to problem-solving. I'm now excited to contribute my skills and expertise to new opportunities in the field of data science, driven by my passion for data-driven insights and analytics.
Hard Skill
Programming Languages
Machine Learning Frameworks
Data Analysis and Visualization
Big Data Tools
Natural Language Processing (NLP)
Data Manipulation and Cleaning
Soft Skill
Observation
Decision making
Communication
Multi-tasking
Education Background
University of Information Technology
Bachelor in Data Science
Completed in 2024
My Contact
********@**.***.***.**
Thu Duc, Ho Chi Minh City
FPT Software Data Scientist Senior - Onsite
03/2023 – 03/2024
Key responsibilities:
Use smart methods to collect and tidy up data from different places to prepare for making machine learning models.
Create and put into action algorithms and models that use machine learning to solve problems in the business.
Find and fix parts of the data to make the models work better. See how well the models are doing using good ways to measure their success.
Change settings to make the models work even better and predict things accurately.
Put the models to work in real situations, making sure they work well, don't break, and can be fixed if something goes wrong.
Work closely with different teams, like the people who collect data, write software, and run the business, to put the models into what they're doing. Keep up with new ideas and ways of doing things in machine learning to solve hard problems.
Nguyễn Minh Tiến
Certificates
Google Cloud Certifications: A Tour of Google Cloud Hands-on Labs Google Cloud Certifications: Big Data and Machine Learning Fundamentals Google Cloud Certifications: Foundations: Data, Data, Everywhere Google Cloud Certifications: A Tour of Google Cloud Hands-on Labs IBM Certifications: Data Visualization and Dashboards with Excel and Cognos IBM Certifications: Excel Basics for Data Analysis IBM Certifications: Introduction to Data Analytics Udemy Certifications: Python for Data Analysis & Visualization Udemy Certifications: Python for Deep Learning: Build Neural Networks in Python GPA: 8.57/10
TienTH
Tien Minh Nguyen
Languages
Vietnamese
English
Technical
R
SQL
Python
C++ Finpros Data Scientist Junior - Hybrid
03/2021 – 01/2023
Key responsibilities:
Assist in collecting, cleaning, and analyzing datasets to derive insights. Support the development of predictive models and create visualizations for communication.
Collaborate with teams and document methodologies to ensure data-driven solutions.
Data Scientist at VinAI Research (January 2020 - October 2021): Developed a Machine Learning Model: Built a sales prediction model with 95% accuracy, aiding the company in optimizing business strategies and inventory management.
Big Data Analysis: Processed and analyzed over 10TB of transaction data, providing deep insights into customer behavior and market trends.
Cost Optimization: Applied cost-benefit analysis to reduce operational costs by 15% through process improvements and automation. Data Analyst at Tiki.vn (December 2021 - June 2022): Market Research: Investigated and analyzed data from over 5 million transactions, proposing strategies that increased revenue growth by 20%.
Advertising Optimization: Used user behavior analysis to optimize advertising campaigns, enhancing ROI by 30%. User Experience Improvement: Developed a personalized product recommendation algorithm, improving customer conversion rates by 10%.
Data Scientist at VNG Corporation (September 2022 - April 2023): Game Data Analysis: Analyzed data from 50 million players to enhance user experience and increase player retention rates. Data Modeling: Constructed a churn rate prediction model with 90% accuracy, assisting the company in developing effective customer retention strategies.
Algorithm Optimization: Improved user classification algorithms, increasing the efficiency of personalized marketing by 25%. Achieved Top 5 in UIT Data Challenge 2023 (March 2023): Team Leadership: Led a team of data scientists and analysts to compete in the prestigious UIT Data Challenge 2023. Strategic Planning: Devised a comprehensive plan outlining project milestones, resource allocation, and timelines to ensure a competitive edge.
Model Selection: Handpicked a robust pretrained model suitable for our dataset, significantly reducing the time-to-deployment. Data Preprocessing: Actively participated in data cleaning, transformation, and augmentation to prepare a high-quality dataset for model training.
Error Analysis: Conducted thorough error analysis post-competition to identify and rectify model weaknesses, providing valuable insights for future projects.
Achievements
Sentiment Analysis Project on Vietnamese Social Media Platforms (May 2021 - November 2021): Objective: To analyze sentiment in user comments on popular Vietnamese social media platforms, focusing on Facebook. Tasks:
Collected and preprocessed a dataset of over 1 million user comments in Vietnamese from Facebook. Implemented Natural Language Processing (NLP) techniques to classify sentiments as positive, negative, or neutral. Utilized a combination of machine learning models, including Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) networks.
Accuracy: Achieved an overall sentiment classification accuracy of 87%. Outcome: The analysis provided valuable insights into public opinion on various topics, which helped businesses tailor their marketing strategies and improve customer engagement.
E-Commerce Customer Lifetime Value Prediction (June 2022 - December 2022): Objective: To predict the lifetime value of customers on an e-commerce platform to improve customer relationship management and increase long-term profitability.
Tasks:
Extracted and cleaned customer transaction data spanning two years from the e-commerce database. Engineered features reflecting purchasing patterns, frequency, monetary value, and recency. Implemented a predictive model using the RFM (Recency, Frequency, Monetary) approach combined with a Gradient Boosting Machine (GBM).
Accuracy: The model predicted customer lifetime value with an accuracy of 90%. Outcome: Enabled the marketing team to segment customers more effectively and allocate resources to high-value segments, resulting in a 25% increase in customer retention rate. Customer Churn Prediction Project:
Tasks: Created a churn prediction model to identify at-risk customers. Accuracy: Reached an accuracy of 89% in predicting churn. Model: Employed Random Forest and Gradient Boosting classifiers. Data Source: Customer usage data from a subscription-based service. Image Recognition Project:
Tasks: Developed an image recognition system to classify and tag images. Accuracy: Achieved a classification accuracy of 95%. Model: Used Convolutional Neural Networks (CNNs) with transfer learning. Data Source: Image datasets from publicly available APIs. Projects
Contact this candidate