Data Scientist Projects

Technical Skills:

• General skills: Exploratory Data Analysis, Time Series Analysis, Hypothesis Testing, ETL, Machine Learning, Deep Learning
• Programming Language: Python, SQL.
• Visualization Tools: Tableau, Looker Studio.
• Libraries / Framework: TensorFlow, Scikit-learn, Streamlit, Pandas, Numpy, Matplotlib, Seaborn, Scipy, Feature-Engine.
• Techniques: NLP, Computer Vision, Time Series Analysis, Forecasting.
• Modeling Algorithms: Regression, Random Forest, Decision Trees, Support Vector Machine (SVM), KKN, Neural Networks, Clustering, and Dimensionality Reduction
• Others: Google BigQuery, Hugging Face, Docker

Education

• Hacktiv8 Bootcamp Jakarta, Indonesia Data Science Program. Score: A(89.48%) | June 2023 - August 2023
• Telkom University Bandung Indonesia Bachelor of Physics Engineering | July 2014– August 2021

PROJECTS

Cyberbullying Tweets NLP Analysis

Developed algorithms using natural language processing and deep learning models for predictive cyberbullying tweets, had the ability to create and deploy predictive models and achieved 72% accuracy score.

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-Learn, TensorFlow, Keras, Streamlit

Company Customer Churn Prediction| July 2023

Developed a machine learning project utilizing Artificial Neural Network to forecast customer churn for a company, based on historical customer data, and achieved a 90% accuracy score

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, SciPy, Scikit-Learn, Feature-Engine, TensorFlow, Keras, Streamlit

Airline Passengers’ Satisfaction Prediction | July 2023

Developed a machine learning project utilizing classification supervised learning to forecast airline passengers’ satisfaction for a company, base on historical passengers data, and achieved a 91% accuracy score

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-Learn, TensorFlow, Keras, Streamlit.

Credit Card Customer Segmentation | August 2023

Developed a clustering segmentation customer of credit card based on the financial behaviour. By using K-Means method, it was found that there are 4 clusters with customers’ characteristics based on its segments.

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, K-Means, Scikit-Learn, TensorFlow, Keras, Streamlit.

Global Suicide Rate Analysis | June 2023

Designed and analyzed the global suicide rate utilizing using hypothesis testing with statistical methods such as t-tests, ANOVA, and chi-square tests, based on historical global suicide rate data

Technology / Tools: Tableau, Python, Pandas, Numpy, Seaborn, Matplotlib, Scikit-Learn, Statsmodels, studiolooker.

Term Deposit for Bank Marketing Prediction

Based on the modeling that has been carried out, the XGBoosting tuning model is the best model for predicting whether a customer will subscribe to a term deposit or not. With an accuracy rate of up to 88%, a classification rate of 89%

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, SciPy, Scikit-Learn, Feature-Engine, TensorFlow, huggingface Keras, Streamlit

TheLook E-Commerce Sales Behaviour

TheLook’s CEO plans to increase sales in the 4th quarter by targeting $250,000 due to mass celebrations like Christmas and New Year. Product categories like intimates, hoodies, sweatshirts, and shorts will be produced to increase sales.

Technology / Tools: Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-Learn.