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I'm
Amin Abasi
Contemplative analyst. Inspired by tough problems.
Who am I?
Hello! I am Amin Abbasi, a data scientist with a passion for analysis.
I’m currently finishing my master’s in Business Analytics at UIC, and I truly understand the challenges that come with navigating data in today’s world. With over five years of experience in analyzing data, I’ve dedicated myself to applying statistical and machine learning techniques to uncover answers and improve processes. I’m passionate about using these skills to make a positive impact and help others succeed.
5+
Yrs Experience
11,000+
Hrs work on Data
12+
Coffee Per Week
Urban Transportation Center at UIC
Data Analyst - Researcher (Sep 2023 until Present - 2 yrs)
At the Urban Transportation Center (UTC) at UIC, I worked as a Data Analyst and Research Assistant, applying machine learning and SQL to improve transportation systems. I developed models for traffic prediction, accident risk analysis, and demand forecasting for both public transit and refrigeration logistics.
I also created a high-performance SQL backend and interactive dashboards in Tableau and Power BI, delivering real-time insights for Illinois transit agencies to support planning and decision-making.
My Work Experiences
DigiKala Online Marketplace
Data Analyst - Business Analyst (Jul 2017 until Jun 2023 - 2 yrs)
At Digikala, one of the largest online marketplaces in the Middle East, I worked as a Business Analyst for nearly six years, leveraging advanced analytics and machine learning to drive business impact.
I spearheaded the development of a fraud detection system using Isolation Forest and BERT models to identify anomalous transactions and fake reviews, significantly enhancing platform trust. I also led the creation of a dynamic pricing optimization model, employing reinforcement learning and competitor-demand data to boost marketplace revenue by 12%. My work involved full-cycle development—from modeling to API deployment and MLOps monitoring—utilizing tools like Python, Azure SQL, and Power BI to deliver scalable, real-time insights and solutions.
BOSCH Company (Internship)
Data Scientist Intern (Jan 2025 until May 2025)
During my internship at Bosch, I collaborated with the Marketing and Data Science teams within the Automotive Aftermarket division. Our project focused on market analysis using time series and marketing data to better understand product demand in the Midwest region of the U.S. We built a data pipeline using Azure SQL Database, Azure Storage, and Azure Data Factory to manage and process the data efficiently. I contributed to the development and implementation of advanced forecasting models, including XGBoost and Temporal Fusion Transformer (TFT), to predict product demand. Additionally, I created an interactive Power BI dashboard to visualize sales trends and conduct competitor analysis, uncovering actionable insights to support Bosch's marketing and business strategies.
My Education
University of Illinois at Chicago
Master of Business Analytics (MSBA) Aug 2023 - May 2025
Islamic Azad University
Bachelor of Electrical Engineering Aug 2014 - Sep 2018
My Skills
Throughout my experiences working on projects at UTC, Digikala, Bosch, and UIC, I've had the opportunity to engage with a variety of tools and techniques in data science. I understand how challenging it can be to navigate this field, and I’ve learned valuable techniques and algorithms that I’m eager to share. I’ve categorized them below:
Programming
SQL, NoSQL, Python (Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Matplotlib, Seaborn), R, HTML, CSS
Data Analysis
Advanced-Data Analysis, EDA, Statistical Methods, Tableau, Power BI, Matplotlib (Python), ggplot2 (R), Statistical storytelling, Explaining insights effectively, Databrick , Azure Data Factory
Modeling
Statistical Methods, Inference Testing, Sampling Techniques, LLMs, RNN & CNN, NLP, Machine Learning Models (Regression, Classification, Clustering, etc.), Time Series Models (ARIMA, LSTM, TFT), Data Mining, A/B Testing
Interpersonal
Problem-solving, Teamwork, Attention to Detail, Critical Thinking, Curiosity, Time Management, Cross-Functional Collaboration
Some Of My Projects
Time Series Forecasting with Traditional & Modern Methods
here are plenty of methods used to forecast a time series. While data characteristics can help point you toward an optimal model, it’s important to weigh the pros and cons of any approach you choose. Traditional models like ...
Exploring Performance Metrics: NFL Combine Analysis
In the National Football League (NFL), athletes exhibit a remarkable range of physical attributes tailored to the demands of their positions. Every year, the NFL Combine collects physical and performance data ....
BERLIN
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Amin Abbasi
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