Hello, my name is Muhammad Enrizky Brillian
I' m a Data Scientist
Muhammad Enrizky Brillian, a Data Engineer at Sanofi, Pursuing Data Science and Machine Learning Specialist at the University of Toronto. Proficient in diverse technologies like PyTorch, TensorFlow, and Tableau, he excels in ML and DL. His impactful projects, such as Human Activity Recognition and Handwritten Digit Recognition, showcase his deep understanding of computer vision. Enrizky's expertise extends to finance, evident in projects like Loan Prediction and Income Prediction models, demonstrating a strong grasp of data-driven strategies. As a Teaching Assistant, he fosters an enhanced learning experience, and his roles as a Big Data Analyst reflect operational efficiency gains. His commitment to innovation is evident in projects like the Podcast Summarizer and GIS Data Science. Enrizky's Tableau dashboards for Saypo Inc. and data-driven job search strategies showcase his ability to present complex insights effectively. Overall, he is a versatile professional, combining academic prowess with hands-on experience, driving innovation in data science and machine learning.
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About Me
I'm Muhammad Enrizky Brillian as a Data Scientist
Muhammad Enrizky Brillian, a Data Engineer at Sanofi, pursuing Data Science and Machine Learning Specialist at the University of Toronto. Proficient in diverse technologies such as PyTorch, TensorFlow, and Tableau, he has led impactful projects like Human Activity Recognition (91% accuracy) and Handwritten Digit Recognition (98% accuracy). Enrizky's roles as a Teaching Assistant and in industry as a Big Data Analyst showcase his ability to optimize databases, reduce operational costs, and enhance decision-making. His commitment to innovation is evident in projects like the Podcast Summarizer and GIS analysis of Toronto apartments. Enrizky's Tableau dashboards for Saypo Inc. and insightful Tableau Story on job search strategies underscore his skills in data presentation. With a dynamic skill set, Enrizky is a versatile professional contributing to the forefront of data science, machine learning, and deep learning.
Website : https://billy-enrizky.github.io/portfolio/
Email : billy.suharno@mail.utoronto.ca
Degree : Data Science and Machine Learning Specialist, Computer Science Major, Economics Minor
Phone : +14167317583
City : Toronto, Ontario
Applied Deep Learning & Machine Learning
Computer Vision
Data Extraction, Transformation, Loading
Data Visualization
Education
2022 - 2025
Bachelor in Data Science and ML Specialist
Funded with Advanced Indonesian Scholarship (BIM) from the Indonesia Ministry of Education, Culture, Research, and Technology (~$380,000, 100% Tuition Fee + living allowances).
Activities:
- ● Teaching Assistant at the University of Toronto
- ● Finance & Data Lab Assistant at the University of Toronto
- ● Academic Representative at the Association of Mathematics and Computer Science Students
- ● University Student Ambassador at the University of Toronto
Experience
January 2024 - Present
Data Engineer at Sanofi
- ● Constructed robust data pipelines utilizing Python and SQL, demonstrating expertise in relational databases such as MySQL, SQL, Oracle, consistently delivered efficient ETL solutions.
- ● Contributed to enhanced data accessibility by executing complex queries, developing user interfaces for data visualization using HTML, CSS, JS, Streamlit, and RShiny web frameworks.
- ● Spearheaded support for diverse data engineering and management initiatives, collaborating seamlessly to fulfill process data requests and enhance data-driven decision-making capabilities.
May 2024 - Present
Research SUDS at UHN
- ● Recognized with a $7200 grant through the Summer Undergraduate Data Science Program by the Data Sciences Institute.
- ● Tasked with developing a novel machine learning model capable of identifying human activity with limited data input.
- ● Engaged in research at the University Health Network under the guidance of Dr. Jose Zariffa.
May 2024 - Present
Research Student at the Computer Science Department, University of Toronto
- ● Engaging in research for the course CSCD94H3Y (Computer Science Project) at the The Computational Health and Interaction (CHAI) Lab under the supervision of Professor Alex Mariakakis and PhD student Georgianna Lin.
- ● The project is titled "Investigating Holistic Gendered Health through Tracking and Physiological Sensors.
September 2022 - December 2022
Big Data Analyst at Kimia Farma
- ● Engineered a SQL database with 140,000+ entries and 30+ columns, optimizing access across 20+ branches, resulting in a remarkable 70% boost in sales distribution efficiency.
- ● Leveraged SQL querying expertise to optimize data ETL, leading to a 33% reduction in data processing time, and directly contributed to a 40% reduction in operational cost.
- ● Designed and developed a Tableau dashboard for sales data, enhancing data accessibility and facilitating data-driven decision-making, saving $95,000 in the annual budget.
March 2022 - July 2022
Data Analyst at Mulia Health Dental Care Group
- ● Conducted comprehensive analysis of customer data across 14 MHDC branches, processing data from over 10,000 customers, resulting in a 15% increase in operational efficiency.
- ● Produced visually intuitive diagrams and charts using Microsoft Excel, simplifying data interpretation for stakeholders and enhancing decision-making capabilities.
- ● Delivered data-driven recommendations to stakeholders using Tableau Story, resulting in the implementation of strategic initiatives that led to a 25% increase in company profitability.
September 2023 - Present
Teaching Assistant at the University of Toronto
- ● Conducted weekly tutorial sessions for a class of 30 students as the sole instructor, ensuring effective learning.
- ● Held regular office hours, providing additional support to students, resulting in improved understanding and performance.
- ● Assisted in grading quizzes, assignments, tests, and exams, ensuring fair and consistent evaluation of student work.
May 2023 - Present
Finance & Data Lab Assistant at the University of Toronto
- ● Developed a Tableau Finance Dashboard showcasing 3 years of Saypo Inc.'s financial performance, leading to enhanced financial transparency and decision-making.
- ● Created detailed line, bar, and area charts for monthly sales, gross profit, net profit margin, and marketing expenses, improving data accessibility and enabling performance trend monitoring.
- ● Implemented user-friendly filters for data exploration, allowing users to analyze specific time periods and conduct regional performance comparisons, resulting in more informed decision-making.
- ● Achieved 98% data completeness by proficiently handling missing values through imputation, ensuring a high-quality dataset for ML model training.
- ● Enhanced model accuracy from 56% to 83% by selecting various ML models and tuning hyperparameters, improving prediction capabilities.
- ● Developed a user-friendly loan prediction application, enabling real-time loan approval predictions and enhancing model accessibility.
- ● Developed and presented an informative Tableau Story on job search strategies in the USA, providing valuable insights into salary trends and job preferences.
- ● Utilized Best Fit Trend Lines to analyze historical salary growth patterns, aiding users in making informed decisions about their future earning potential.
- ● Leveraged Tableau Calculated Field to analyze price parity for job destinations, assisting job seekers in optimizing their career choices.
- ● Utilized Random Forest Classifier to develop an ML model, achieving an outstanding 84.92% accuracy rate on test data, showcasing superior predictive performance.
- ● Performed extensive data preprocessing, resulting in a remarkable 95% reduction in feature dimensionality, enhancing model accuracy and reducing data complexity.
- ● Utilized PySpark to process and analyze a Google Play Store dataset with 10,000+ rows, delivering a 10-fold increase in data processing speed compared to Hadoop.
- ● Conducted in-depth data analysis using PySpark, identifying top-rated apps, most-installed apps, and category-wise installation trends, contributing to strategic decision-making.
Services
Data Analysis
"Unlock insights and drive decisions with my Data Analysis services. From boosting sales efficiency by 70% to enhancing operational performance, I'm your data partner for success. Contact me today!"
Data Engineering
"Elevate your data infrastructure with my Data Engineering expertise. From SQL databases to ETL optimization, I streamline data for actionable insights. Let's power your analytics!"
Data Visualization
"Transform your data into compelling stories with my Data Visualization expertise. From charts to dashboards, I bring insights to life. Let's make your data meaningful!"
Machine Learning
"Unlock the potential of Machine Learning! I offer expert ML services, from predictive modeling to AI solutions. Transform your data into actionable insights with me!"
Business Analysis
"Elevate your business with my Business Analysis services. From optimizing operations to data-driven insights, I've got the solutions. Contact me for transformative results!"
Teaching Assistant
"Elevate your learning experience with my dedicated Teaching Assistant service. Extensive expertise, personalized guidance, and unwavering support to boost your academic success. Let's excel together!"
Portfolio
My Selected Projects :
DCGAN Face Generator
- ● Implemented DCGAN with PyTorch to generate realistic faces, training the model on a dataset of 21,551 manually resized face images (64x64 pixels) for optimal performance.
- ● Designed and implemented a well-balanced Discriminator Neural Network with 2.7 million parameters and a Generator Neural Network with 3.8 million trainable parameters.
- ● Developed a comprehensive approach for efficient data preprocessing, including resizing and batch normalization, coupled with GPU acceleration (CUDA) for rapid training performance.
Deep Learning: Human Video Activity Recognition
- ● Implemented a Deep Learning Human Activity Recognition system using a hybrid CNN and LSTM architecture, resulting in accuracy by 91% on the testing dataset.
- ● Developed the preprocessing pipeline by implementing normalization and frame extraction, resulting in a 25% reduction in overfitting and enhancing the model generalizability.
- ● Implemented a LRCN architecture, seamlessly integrating spatial and temporal features, demonstrating a deep understanding of computer vision and sequential data processing.
Deep Learning: Image Caption Generator
- ● Implemented a customized bidirectional LSTM with attention mechanisms and tokenization for text analysis, achieving a BLEU score of 0.54, showcasing advanced NLP concepts.
- ● Utilized transfer learning with pre-trained VGG16 for effective image features extraction, showcasing expertise in integrating diverse neural networks for superior performance.
- ● Successfully integrated image processing techniques, encompassing extracting, loading, and preprocessing, to demonstrate a comprehensive approach to images data handling.
Deep Learning: Handwritten Digit Recognition
- ● Trained a convolutional neural network (CNN) model to recognize handwritten digits using the MNIST handwritten digit dataset, achieving a high accuracy of 98% on the test dataset.
- ● Significantly accelerated model training by implementing GPU (CUDA) utilization, harnessing parallel processing to achieve a 3x reduction in training time for deep learning models.
- ● Processed and analyzed 70,000 handwritten digit images with PyTorch, including data loading and transformation, showcasing strong skills in handling large datasets.
Deep Learning: Image Classification
- ● Developed a machine learning model using TensorFlow and Keras, achieving significant accuracy improvements from 56% to 84%, in a dataset consisting of 60,000 color images.
- ● Employed convolutional neural network (CNN) with batch normalization, dropout, and various convolution layers, resulting in a deep learning model with 2,397,226 parameters.
- ● Analyzed and presented results through visualizations, including classification report and confusion matrix, demonstrating strong data analysis and reporting skills.
Deep Learning: Speech Emotion Recognition
- ● Trained and implemented an LSTM neural network architecture with 77,160 trainable parameters, achieving outstanding accuracy of 98.61% on the testing dataset.
- ● Engineered a robust data preprocessing pipeline, including the function, extract_mfcc, to calculate Mel-frequency cepstral coefficients (MFCCs) of audio files from librosa audio library.
- ● Innovatively integrated a user-friendly Streamlit version, enabling one-click emotion recognition for users, enhancing accessibility to the developed SER model.
Loan Prediction Machine Learning Model
- ● Achieved 98% data completeness by proficiently handling missing values in critical columns through imputation using NumPy and Pandas, ensuring a pristine dataset for ML model training.
- ● Enhanced model accuracy from 56% to 83% by meticulously selecting various ML models from Scikit-learn and tuning the hyperparameter, through data-driven strategies.
- ● Developed a user-friendly loan prediction application, facilitating real-time loan approval predictions for users and enhancing model accessibility and usability.parisons, resulting in more informed decision-making.
Income Prediction ML Random Forest Model
- ● Utilized Random Forest Classifier to develop an ML model, yielding an outstanding 84.92% accuracy rate on the test data, showcasing superior predictive performance.
- ● Performed extensive data preprocessing, encompassing One-hot Encoding for multi-class features, resulting in a remarkable 95% reduction in feature dimensionality.
- ● Leveraged correlation analysis and feature importance to pinpoint the top 5% of critical features among 90+ columns, enhancing accuracy score and reducing data complexity by 75%.
Tableau Finance Profit & Loss Dashboard
- ● Developed a Tableau Finance Dashboard, showcasing Saypo Inc.'s 3 years financial performance, featuring interactive visualizations of Profit and Loss Statements, Sales, and Profit Margins.
- ● Created detailed line, bar, and area charts to illustrate monthly Sales, Gross Profit, Net Profit Margin, and Marketing Expenses, enabling users to monitor performance trends effectively.
- ● Implemented user-friendly filters for data exploration, allowing users to analyze specific time periods and conduct regional performance comparisons on the dashboard.
Podcast Summarizer Project
- ● Achieved reliable retrieval of podcast episode details and audio transcription through efficient use of HTTP requests and headers, enhancing the overall performance of the Podcast Summarizer.
- ● Engineered an intuitive user interface for the Podcast Summarizer using Streamlit, enabling users to easily input episode IDs and download episode summaries with a single click.
- ● Led the initiative to develop a resilient API communication system, streamlining interactions with both AssemblyAI and Listen Notes APIs to achieve seamless integration.
Kimia Farma Sales Dashboard Replica
- ● Engineered a SQL database with 140,000+ entries and 30+ columns, optimizing access across 20+ branches, resulting in a remarkable 70% boost in sales distribution efficiency.
- ● Leveraged SQL querying expertise to optimize data ETL, leading to a 33% reduction in data processing time, and directly contributed to a 40% reduction in operational cost.
- ● Designed and developed a Tableau dashboard for sales data, enhancing data accessibility and facilitating data-driven decision-making, saving $95,000 in the annual budget.
Database Driven Web Application
- ● Implemented a secure Flask web application with SQLAlchemy, ensuring data confidentiality through a secret key and SQLite database encryption.
- ● Facilitated seamless user interaction by developing dynamic web routes, allowing users to perform Create, Read, Update, and Delete (CRUD) operations on tasks.
- ● Elevated the user experience by incorporating Bootstrap for a responsive design and Animate.css for modern animation effects, resulting in an engaging Task Manager application.
Tableau Story: Job Search Strategy
- ● Developed and presented an informative Tableau Story titled "Searching For a New Job in USA," providing valuable insights into salary trends, VISA class impact, and job preferences.
- ● Utilized Best Fit Trend Lines to analyze historical salary growth patterns, aiding users in making informed decisions about their future earning potential.
- ● Leveraged Tableau Calculated Field to analyze price parity to identify the most financially advantageous job destination, helping job seekers optimize their career choices.
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Data Analysis of Google Play Store Applications Using PySpark
- ● Utilized PySpark to effectively process and analyze a Google Play Store dataset with 10,000+ rows, delivering a 10-fold increase in data processing speed compared to Hadoop.
- ● Conducted in-depth data analysis using PySpark, identifying top-rated apps, most-installed apps, and category-wise installation trends, contributing to strategic decision-making.
Bikeshare Data Analysis in Toronto Using R Programming Language
- ● Developed data analysis skills through analyzing and visualizing bikeshare data for the Greater Toronto Area (from open.toronto.ca) using R programming language.
- ● Conducted exploratory data analysis by creating tables and graphs to identify trends in bikeshare usage, informing business decisions for bikeshare companies and city officials.
- ● Demonstrated proficiency in data wrangling and cleaning, including handling missing data, transforming data types, and merging datasets to create a comprehensive analysis.
Folium Toronto Apartment Evaluation
- ● Created a comprehensive analysis of apartment building evaluations, achieving a 98% data completeness rate by proficiently managing missing data with Pandas and NumPy.
- ● Developed an interactive Folium map displaying apartment evaluation scores categorized into five distinct classes with unique marker colors, accompanied by a custom legend.
- ● Identified spatial clusters of high and low-quality apartment buildings in diverse Toronto regions, providing critical insights for urban planning and policy formulation.
Contact Me
Have You Any Questions ?
I'M AT YOUR SERVICES
Call Me On
+14167317583
Office
Toronto, Ontario, Canada
billy.suharno@mail.utoronto.ca
Website
https://billy-enrizky.github.io/portfolio/