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Data Science with less than a year in Artificial Intelligence, Machine Learning, and Data Analysis
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Assessing your cultural and operational fit
Information Technology student with a strong interest in artificial intelligence, machine learning, and data analysis. Experienced in data preprocessing, exploratory data analysis, and building basic machine learning models using Python. Actively learning end-to-end AI/ML workflows including feature engineering, model evaluation, and optimization. Highly motivated to learn and contribute in a professional environment with strong analytical thinking and problem-solving skills.
Brawijaya University
Information Technology · Information Technology
N/A – Present
Customer Segmentation
June 1, 2026 – Present
Performed customer segmentation using Hierarchical Clustering to group customers based on behavioral & demographic attributes for pattern analysis.
Health Status Classification of Coffee Consumers
June 1, 2026 – Present
Implemented a Random Forest classification model to classify the health status of coffee consumers based on consumption patterns and health attributes.
Investment Recommendation
June 1, 2026 – Present
Created a rule-based expert system in Prolog to recommend investment options based on user risk profiles.
Customer Retention Prediction
June 1, 2026 – Present
Built classification models (Logistic Regression, Decision Tree, Random Forest) using PySpark and HDFS to analyze customer retention.
Diabetes Patient Prediction Model
June 1, 2026 – Present
Developed a machine learning model in Python to predict diabetes likelihood based on patient data.
Data Science
Dicoding IDCamp
June 1, 2026 – Present
Database Design & Database Programming
Oracle Academy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a breadth of interests within data science, from investment recommendations to health status classification and customer retention. Involvement in various university organizations and a UI/UX design competition win indicate a proactive and collaborative spirit. However, the candidate's experience is entirely academic, which might require adjustment to a professional work culture.
Soft Skills & Operational Fit
The candidate's profile highlights strong analytical thinking, problem-solving, critical thinking, and a willingness to learn, which are crucial for a data science role. Experience as a teaching assistant and involvement in organizational roles suggest good communication and collaboration skills. However, the lack of professional experience means operational fit in a corporate environment is yet to be proven.