Hi, I'm Jihad Akbar

Data Science Enthusiast

Aspiring Data Scientist passionate about machine learning, skilled in Python, SQL, and data visualization. Eager to leverage my technical expertise to create innovative, data-driven solutions.

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Jihad Akbar

About Me

Personal Info

Career Summary

Detail-oriented Machine Learning Annotator with over 1 year of experience at a leading computer vision company, specializing in precise image and video annotation to support machine learning models. Certified in data science, analytics, and engineering, with expertise in Python, SQL, and data visualization tools.

Driven to leverage my technical skills in data science, machine learning, or AI engineering to optimize model performance, enhance data quality, and contribute to innovative, data-driven solutions in a dynamic environment.

Skills

Python SQL Machine Learning Deep Learning Time Series Forecasting Exploratory Data Analysis Data Visualization Tableau Power BI Streamlit GIT Docker TensorFlow PyTorch AWS Azure IBM

Languages

Indonesian
Native
English
IELTS 7.0 (C1)

Work Experience

Machine Learning Annotator Internship

Oct 2024 - Present
PT Nomura Research Institute Indonesia
  • Evaluated AI predictions in a gas station safety project by categorizing 200 daily images and videos into risk levels (low, medium, high) and classifying outcomes as true positive, true negative, false positive, or false negative, ensuring adherence to safety rules.
  • Identified vehicle and carry can properties, detected anomalies, and provided feedback that improved model accuracy from 80% to 95%.
  • Labeled images with false positives and false negatives using bounding boxes and segmentation for 50 images daily, maintaining an annotation accuracy of 95%-100%.

Project-Based Data Science Internship

Feb 2025 - Feb 2025
Bukit Vista Hospitality Services
  • Developed an eye disease classifier for cataract, diabetic retinopathy, glaucoma, and normal conditions. Performed extensive image preprocessing, including checks for class distribution, image size, duplicates, corruption, blurriness, exposure issues, distortions, and noise, ensuring data quality for model training.
  • Built and fine-tuned deep learning models, selecting InceptionV3 with 83% accuracy as the optimal solution. Implemented techniques like early stopping and layer unfreezing for performance improvement, then deployed the model to production using Streamlit on the Hugging Face platform.

Data Annotator

Feb 2024 - Sep 2024
CVAT.ai Corporation, Palo Alto, California, United States
  • Annotated images using CVAT's brush tool at an average pace of 15 minutes per image, accurately outlining paths for a robot lawnmower. Managed diverse annotation classes, achieving an average annotation accuracy of 90%.
  • Reclassified over 10,000 annotated categories into specific subclasses, such as Natural objects into tree crown, high grass, rock, etc., and applied bounding boxes for selected categories.
  • Validated annotations from approximately 30 team members, maintaining an accuracy rate of 90-100% through rigorous validation processes and providing feedback that improved annotation quality and consistency by 20-50% across the team.

Data Projects

Time-Series Forecasting (Olist E-Commerce)

Built time series forecasting model to optimize inventory and revenue planning by accurately predicting daily order volumes and revenue trends.

Time-series forecasting Automatic Forecast SARIMA
View Project

Delivery Time Prediction (Zomato's Operations)

Predicted delivery time with XGBoost (RMSE: 4.29 minutes), compared expected time, distance, and speed using OSRM API, and generated a report on underperforming drivers.

Delivery Time Prediction API XGBoost
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Eye Disease Classifier

Developed a deep learning model to classify cataract, diabetic retinopathy, glaucoma, and normal conditions with 83% accuracy.

Computer Vision Deep Learning InceptionV3
View Project

Churn Analysis

Developed a churn prediction model with XGBoost, achieving 91% recall, 70% precision, and 79% F1-score, delivering actionable insights for business.

Churn Prediction XGBoost Recall
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RFM Analysis for Customer Segmentation in Automobile Sales

Conducted RFM analysis to segment automobile customers, creating 9 segments with actionable insights and a Power BI dashboard for visualizing KPIs.

RFM Analysis Customer Segmentation Power BI
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Credit Card Fraud Detection

Built a precision-optimized model for fraud detection using anonymized transaction data, addressing class imbalance, and achieving a PR AUC of 0.812 and an F2 score of 0.794.

Fraud Detection Precision-Recall AUC Class Imbalance
View Project

New York City Taxi Trip Duration

Predicted NYC taxi trip durations with LightGBM, achieving an RMSLE of 0.55 and identifying trip patterns using K-Means clustering.

Taxi Trip Duration LightGBM K-Means Clustering
View Project

Education & Certifications

Education

Data Science Bootcamp

Oct 2024 - Present
Dibimbing.id
  • Comprehensive program focused on data science and machine learning, covering essential skills in data analysis, data visualization (Tableau and Power BI), predictive modeling, and programming (Python and SQL).
  • Hands-on experience in real-world projects to build a robust data science portfolio.

BSc in Physics

Aug 2016 - Jul 2020
Physics Department of Universitas Sebelas Maret, Surakarta, Indonesia
  • Graduated Cum Laude, GPA: 3.75/4.00
  • Relevant Coursework: Statistical Physics, Physics Computation, Numerical Analysis, Physics-Based Modeling and Simulation

Certifications

Python for Everybody Specialization

University of Michigan • Jan 2024

Deep Learning Specialization

DeepLearning.AI • Apr 2023

Machine Learning Specialization

Stanford University and DeepLearning.AI • Mar 2023

Get In Touch

Contact Information

Location

Jakarta, Indonesia

Email

jihadakbr@gmail.com

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