Human Resources Machine Learning

NGUYEN DUONG TUAN

DATA ANALYST/DATA SCIENTIST

+847******** ******************@*****.*** Github CAREER OBJECTIVE

As an entry-level data enthusiast, I am eager to contribute my analytical skills to a dynamic team. I am committed to continuous learning and excited to apply data-driven insights to real-world challenges. My goal is to grow professionally while making a meaningful impact in the field of data analysis. SKILLS

Data Analysis: Apply statistical and exploratory analysis techniques to extract insights from data. Data Processing & Wrangling: Clean, transform, and prepare data for analysis using Python and SQL. Data Visualization: Create compelling charts, graphs, and dashboards using tools like Power BI and Tableau to communicate insights effectively.

Database Management: Experienced in Data Modelling and Data Warehousing. Familiar with on-premiere services like MySQL, SQL Server and cloud-based services like Azure SQL Database. Machine Learning Fundamentals: Understand and apply basic machine learning concepts to solve business problems. Data Pipelines: Knowledge of data extraction, transformation, and loading (ETL) or extraction, loading, and transformation (ELT) processes for efficient data movement. MY PROJECT

1. Project FPT Customer Sentiment Analysis

Objective: Leverage machine learning and AI to analyze customer sentiment and enhance service satisfaction. Technical Skills: Python, Power BI, Natural Language Processing (NLP), phorBert, MongoDB Data Extraction Description:

- Extracted customer comment data from MongoDB using Python.

- Developed a machine learning model using the phorBert algorithm to classify customer comments.

- Analyzed customer sentiment based on their comments and usage patterns.

- Identified areas for improvement in service quality and customer satisfaction. Value:

- Provided data-driven insights to improve customer satisfaction and reduce churn.

- Enabled FPT to make informed decisions to enhance customer experience and service offerings. Github: Here

2. Project: Stroke-Prediction

Objective: Utilize machine learning algorithms to develop a predictive model for stroke diagnosis, enhancing early detection and improving patient outcomes.

Technical Skills: Python, Jupyter notebook,Flask,HTML,CSS,Machine Learning Description:

- Retrieved stroke data from the Kaggle website for analysis.

- Conducted Exploratory Data Analysis (EDA) and visualized data patterns with python.

- Processed the data by handling missing values, normalizing, and encoding features.

- Employed various machine learning algorithms, including Logistic Regression, Random Forest, SVM, and XGBoost, to build predictive models.

- Evaluated model performance using accuracy, precision, recall, F1-score, and ROC curve analysis. Value:

- Developed a robust application that aids in the early diagnosis of strokes, potentially saving lives.

- Provided healthcare professionals with data-driven insights to enhance decision-making and treatment strategies.

- Improved patient outcomes through timely intervention and improved healthcare services. Github: Here

3. Project: The Customer Segmentation

Objective: Segment customers using RFM analysis for targeted marketing campaigns. Technical Skills: Python, RFM( Recency, Frequency, Monetary), Segmentation, Campaign Development.

Description:

- Analyzed 3 months of customer purchase data using RFM.

- Segmented customers into five distinct groups: VIP, Loyal, New Customers, Lost Customers.

- Developed targeted marketing campaigns for each segment. Value: Demonstrated expertise in customer data analytics to drive business improvement and enhance marketing effectiveness.

Github: Here

4. Project: Cost optimisation and Website performance of the E-commerce company Objective: Optimize costs and website performance for an e-commerce company. Technical Skills: MySQL, PowerPoint

Description:

- Analyzed marketing campaign data to identify effective channels and target customer segments.

- Strategically allocated budget to maximize reach and impact.

- Recommended website improvements based on customer journey and purchase history, enhancing user experience and driving sales.

Value:

- Provided valuable insights to help the company optimize marketing budgets and improve campaign effectiveness.

- Enhanced service quality and customer satisfaction through a better shopping experience on the website. Github: Here

EDUCATION

University Ho Chi Minh City of Industry and Trade

Major:Data Analysis

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