Open to work
DATA ANALYST & machine learning
linkedin.com/in/azzrial-arfiansyah-a97407285
+6287872788220
Jakarta, Indonesia
Summary
A highly motivated and detail-oriented Information Systems undergraduate at UPN Veteran Jakarta, with strong interest and hands-on experience in data analytics, data science, and machine learning. Proficient in data cleaning, exploratory data analysis, statistical modeling, and interactive data visualization using tools such as Python, Power BI, Tableau, and SQL-based databases. Skilled in applying various machine learning techniques including classification, clustering, and time series prediction to generate meaningful insights and support data-driven decision-making.
Actively involved in academic and independent projects, including stock price prediction using LSTM, customer segmentation with RFM analysis, and clustering life expectancy data using DBSCAN. Familiar with data engineering workflows such as data preprocessing, transformation, and deployment using platforms like Streamlit and Google Colab. Currently seeking an internship opportunity in the fields of data analysis, data science, or machine learning to further develop technical expertise while contributing real value through innovative data solutions.
Project & Organization Experience
ksm ANDROID UPNVJ
2024 - Present
KSM Andorid UPNVJ
At KSM Android UPN Veteran Jakarta, I studied data science from the fundamentals to the beginner level, covering topics such as exploratory data analysis (EDA), machine learning, deep learning, and data visualization. I worked on several machine learning projects using Python, both independently and collaboratively. In addition to the academic aspect, I was also actively involved in organizing and participating in the community’s social initiatives.
— Built end-to-end ML pipelines for time series forecasting, clustering, and classification using real-world datasets.
— Predicted Microsoft (MSFT) stock prices with LSTM and deployed results via Streamlit.
— Applied DBSCAN to cluster countries by life expectancy and identify health-related patterns.
— Classified air quality levels using Logistic Regression, Random Forest, and XGBoost based on environmental and pollution features.
— Utilized Python, pandas, scikit-learn, TensorFlow, XGBoost, and visualization tools for analysis, modeling, and evaluation.
Personal project
2025
Analyst & Visualization
This personal project was driven by my curiosity and desire to explore deeper into the fields of data visualization, machine learning, and deep learning. It also served as an opportunity to expand my understanding of new tools and frameworks.
— Cleaned and prepared data using Google Colab/Jupyter (handled duplicates, nulls, and formatting)
— Calculated budget realization percentages and categorized regional performance
— Engineered RFM (Recency, Frequency, Monetary) features for customer segmentation
— Performed univariate, bivariate, and multivariate exploratory data analysis (EDA)
— Designed interactive dashboard layouts using Figma
— Imported data into Power BI and calculated RFM scores using DAX
— Built customer segments and visual dashboards in Power BI
— Extracted insights to support marketing strategies and regional policy recommendations
Teaching Assistant upnvj
2025
Database System Practicum
I was accepted as a teaching assistant for the Database course in February. In this role, I was responsible for supporting the lecturer through teaching, reporting, and preparing materials. Beyond strengthening my relationship with the lecturer, this experience also expanded my knowledge and allowed me to learn from other students and the academic environment.
— Assisted the lecturer during practical sessions by guiding students through exercises and resolving technical issues
— Prepared teaching materials, including modules containing exercises and assignments
— Created and compiled student attendance reports
— Facilitated discussions to strengthen students understanding of database concepts
— Collaborated with fellow assistants to divide responsibilities in developing teaching materials
— Contributed to improving the structure and delivery of practical materials based on student feedback
Skills & Tech Stack
Data Cleaning & Preprocessing
Team collaboration
Data Processing
High discipline & responsibility
Data Modeling
Quick adaptability
Data Visualization
Strong communication
Data Analysis & Insight Extraction
Jupyter
Pandas
Power BI Dekstop
Python
MySQL
PostgresSQL
Excel
Matplotlib
Numpy
Scikit-Learn
Tensorflow
Github
Streamlit
Tableau
Git
Languages
Indonesia
English
Certificates
Certiport
KSM Android UPNVJ
Links
azzriala@gmail.com
+6287872788220
