Curriculum Vitae
Reyzha Siva Dewi
Fresh graduate in Statistics and Data Science at IPB University with strong interest in Data Analytics, Predictive Modeling, Data Visualization, and Machine Learning. Experienced in completing 15+ data analysis projects using R, Excel, Python, C++, and SQL. Skilled in transformaing data into actionable insights to support decision-making.
Agustus 2025
Institut Pertanian Bogor
S1 • Statistika dan Data Sains • IPK 3.44
September 2024 - Desember 2024
Data Scientist
PT Telekomunikasi Indonesia (Persero) Tbk • Magang
Conducted research on microclimate modeling to provide a theoretical foundation for greenhouse management and agricultural digitalization.
Developed a Sigmoid Growth Model using tomato growth data to predict plant growth and determine optimal treatment strategies.
Particapated in the Ayo Beraksi program through the MACu Tani initiative, which achieved first place in the Aksi Bumi category for sustainable agricultural solutions.
Served as design team member for MACu Tani, creating visual materials with Figma and Canva to support presentations and outreach.
Reviewed AI proposal designs, focusing on originality, societal impact, and technical feasibility to deliver actionable insights for future innovation projects.
Media
Mei 2024 - Juni 2024
Surveyor of Research and Development Department
TRANS 7 • Contract Base
Conducted face-to-face interviews on Ramadan TV viewing habits with 25+ respondents in Depok and Jakarta.
− Performed data entry on survey results and confirmation from 40+ survey questions.
Maret 2024 - April 2024
Surveyor of Public Survey 2024
Gamma Sigma Beta (GSB) IPB • Project Base
Conducted an online survey on Artificial Intelligence: Assessing the Trust, Knowledge, and Perception of the Jabodetabek
Community with 8+ respondents.
Media
Januari 2024 - Desember 2024
Staff of Survey and Research Department
Gamma Sigma Beta (GSB) IPB • Organisasi
Led the technical team for a public survey 2024 of 60 surveyors to find 600 respondents on the topic of the relationship
between music and human development in Jabodetabek community.
− Served as a mentor on the topic of variability and reliability testing for pra-surveys to 10+ members of the Survey and
Research Department.
September 2023 - Oktober 2023
Secretary and Treasurer of Scretarial and Assessment Division
G-Awarding Night • Organisasi
− Helped coordinate 8 members of secretarial and assessment division.
− Successfully managed executive calendar using Google Calendar.
− Managed certificate production for 10+ winners, 40+ honorees, and 60+ committee using Canva, Excel, and Word.
− Managed financial budgeting and reporting using Google Spreadsheet
Juni 2023 - Oktober 2023
Secretary and Treasurer of Event Organizer Division
Statistics Junior Competition • Organisasi
− Successfully managed executive calendar using Google Calendar.
− Managed and organized administrative support for senior management and team members.
− Coordinated a webinar and expo on "Unleashing the Power of Statistical Imagination" with 100+ participants from
Indonesian high school students.
− Managed financial operations, imcluded budgeting and reporting
Januari 2023 - Desember 2023
Staff of Social and Environment Department
BEM FMIPA IPB • Organisasi
Led 10 members of the social and environmental department in the Share the Nutrion program, which was held twice a
month with 40+ participants in an event.
− Managed a conservation camp event with a focus on biodiversity mapping at PPKA Bodogol with 10+ participants.
− Managed a curriculum program as part of a community service program that focused on increasing environmental
awareness for 100+ elementary school students.
− Published an instagram post once a month focusing on environmental and social issues.
Juni 2024
Belajar Analisis Data dengan Python
Dicoding • 81P2NOWKOXOY
Dasar-Dasar Analisis Data: memahami berbagai konsep dasar analisis data beserta tahapannya (2 Jam 15 Menit).
Penerapan Dasar-Dasar Descriptive Statistics: mengetahui konsep dasar descriptive statistics dan penerapannya dalam proses analisis data (2 Jam 50
Menit).
Pertimbangan dalam Pengolahan Data: mengidentifikasi berbagai hal penting yang harus diperhatikan ketika mengolah data (1 Jam 50 Menit).
Data Wrangling: mengimplementasikan berbagai teknik data wrangling guna menyiapkan data yang bersih dan siap dianalisis. (3 Jam 50 Menit).
Exploratory Data Analysis: menerapkan berbagai teknik EDA guna memperoleh gambaran terkait data yang dianalisis (3 Jam 20 Menit).
Data Visualization: Menerapkan berbagai teknik visualisasi data yang efektif guna mempermudah penyampaian hasil analisis data (3 Jam 50 Menit).
Pengembangan Dashboard: membuat dashboard menggunakan streamlit sebagai media penyampaian hasil analisis data yang interaktif (4 Jam 15
Menit).
Juni 2024
DeepLearning.AI TensorFlow Developer
DeepLearning.AI • https://coursera.org/verify/profession al-cert/9CBYBNHCQRTC
Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for computer vision applications.
Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
Build natural language processing systems using TensorFlow.
Apply RNNs, GRUs, and LSTMs as you train them using text repositories
Media
Juni 2024
Structuring Machine Learning Projects
DeepLearning.AI • https://coursera.org/verify/BTPLYD9RK28Z
Juni 2024
TensorFlow: Advanced Techniques
DeepLearning.AI • https://coursera.org/verify/specialization/TXHEZ235ERHA
Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers.
Learn optimization and how to use GradientTape & Autograph, optimize training in different environments with multiple processors and chip types.
Practice object detection, image segmentation, and visual interpretation of convolutions.
Explore generative deep learning, and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to GANs.
Juni 2024
Generative AI for Everyone
DeepLearning.AI • https://coursera.org/verify/XLN3868FQPDY
What generative AI is and how it works, its common use cases, and what this technology can and cannot do.
How to think through the lifecycle of a generative AI project, from conception to launch, including how to build effective prompts.
The potential opportunities and risks that generative AI technologies present to individuals, businesses, and society.
Media
Juni 2024
TensorFlow: Advanced Techniques
DeepLearning.AI • https://coursera.org/verify/specialization/TXHEZ235ERHA
Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers.
Learn optimization and how to use GradientTape & Autograph, optimize training in different environments with multiple processors and chip types.
Practice object detection, image segmentation, and visual interpretation of convolutions.
Explore generative deep learning, and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to GANs.
Mei 2024
TensorFlow: Data and Deployment
DeepLearning.AI • https://coursera.org/verify/specialization/QB2D4QVQL8SZ
Run models in your browser using TensorFlow.js
Prepare and deploy models on mobile devices using TensorFlow Lite
Access, organize, and process training data more easily using TensorFlow Data Services
Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard
April 2024
Machine Learning
DeepLearning.AI • https://coursera.org/verify/specialization/3HJTBTSTRQ4B
Build ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression)
Build & train a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods
Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection
Build recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model
Maret 2024
Mathematics for Machine Learning
DeepLearning.AI • https://coursera.org/verify/specialization/YG8AYBUM6YE5
A deep understanding of the math that makes machine learning algorithms work.
Statistical techniques that empower you to get more out of your data analysis.
Maret 2024
Share Data Through the Art of Visualization
Google • https://coursera.org/verify/5FCNRC4BZUY5
Describe the use of data visualizations to talk about data and the results of data analysis.
Identify Tableau as a data visualization tool and understand its uses.
Explain what data driven stories are including reference to their importance and their attributes.
Explain principles and practices associated with effective presentations.
Maret 2024
Analyze Data to Answer Questions
Google • https://coursera.org/verify/LC5BU4EGWL4R
Discuss the importance of organizing your data before analysis by using sorts and filters.
Convert and format data.
Apply the use of functions and syntax to create SQL queries to combine data from multiple database tables.
Describe the use of functions to conduct basic calculations on data in spreadsheets.
Media
Maret 2024
Process Data from Dirty to Clean
Google • https://coursera.org/verify/V7J8M4BA4STF
Define different types of data integrity and identify risks to data integrity.
Apply basic SQL functions to clean string variables in a database.
Develop basic SQL queries for use on databases.
Describe the process of verifying data cleaning results
Februari 2024
Using Python to Interact with the Operating System
Google • https://coursera.org/verify/NRUB47T3DAFE
Setup, configure, and use your own developer environment in Python
Manipulate files and processes running on the Operating System using Python
Understand and use regular expressions (regex), a powerful tool for processing text files
Know when to choose Bash or Python, and create small scripts using Bash
Februari 2024
Introduction to Git and GitHub
Google • https://coursera.org/verify/JWRD7KNTD62B
Understand why version control is a fundamental tool for coding and collaboration
Install and run Git on your local machine
Use and interact with GitHub
Collaborate with others through remote repositories
Media
Februari 2024
Crash Course on Python
Google • https://coursera.org/verify/K5T57A3P7N8V
Understand what Python is and why Python is relevant to automation
Write short Python scripts to perform automated actions
Understand how to use the basic Python structures: strings, lists, and dictionaries