Frida Putriassa, fresh graduate majoring in Information Systems, specializing in the domains of data collecting, analysis, visualization, and modeling. Proficient in Python, R, SQL, and Advanced Excel. Dedicated to facilitating data-driven decision-making processes. A resourceful problem solver with a collaborative spirit and actively pursuing opportunities in data analysis or data science.
Extracting insights from complex datasets to inform strategic decisions, using tools like SQL and Python for efficient data processing and analysis.
Creating compelling visual representations of data with Tableau, Power BI, and Looker Studio to communicate findings effectively.
Building and deploying ML models using Scikit-Learn and PyTorch for predictive analytics and recommendation systems.
Universitas Pembangunan Nasional "Veteran" Jakarta
Aug 2021 - July 2025
Bachelor Degree in Information System, Minor in Data Science
GPA: 3.92 / 4.00
Relevant Coursework: Data Science, Data Warehouse and Data Management, Big Data, Data Management,
Business Intelligence, Artificial Intelligence, Financial Technology.
Generated 4 years of synthetic data from 39 provinces and 459 cities, modeled into a 115-table Data Vault with PostgreSQL/DBeaver, and built 12 Superset dashboards validated with VLAT (80% comprehension), boosting decision accuracy by 40%.
Applied ACO algorithm with 6 destinations in Cirebon, 10 ants, and 100 iterations, yielding a highly efficient route of 3.33 units and visually presented using Matplotlib library.
Developed a recommendation system by applying machine learning to refine and personalize suggestions based on various factors within MyDramaList dataset (2015-2023) through Exploratory Data Analysis (EDA).
Built an interactive dashboard on Google Data Studio/Looker Studio, integrating predictive insights, tree maps, and pivot data on passenger data for analyzing service improvements and capacity expansion.
Credit card applicant analysis built with Looker Studio, showcasing demographic and income distribution insights. Visualizations reveal dominant applicant groups, key income disparities, and correlations between education, family size, and housing.
I'm always interested in new opportunities and collaborations. Feel free to reach out if you'd like to work together!
Let's create something amazing together!