Azizul Islam
Data Analyst at Iowa Extension
Former Textile Engineer and former international school analytics teacher. Always analytical.
I love SQL and finding patterns in data and solving hard problems.
I've lived in 50 countries and traveled to many more.
Data Scientist
Technical Skills: Python, SQL, AWS, Snowflake, MATLAB
Education
- MS in Statistics – Iowa State University – Ames, IA, USA (Pursuing)
- MS in Merchandising – Oklahoma State University – Stillwater, OK, USA (Aug, 2020)
- BS in Textile Engineering – Bangladesh University of Textiles – Dhaka, BD (Mar, 2015)
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M.S., Statistics Iowa State University (May 2022) -
M.S., Merchandising Oklahoma State University (December 2019) -
B.S., Textile Engineering Bangladesh University of Textiles (May 2017)
Work Experience
Data Scientist @ Toyota Financial Services (June 2022 - Present)
- Uncovered and corrected missing step in production data pipeline which impacted over 70% of active accounts
- Redeveloped loan originations model which resulted in 50% improvement in model performance and saving 1 million dollars in potential losses
Data Science Consultant @ Shawhin Talebi Ventures LLC (December 2020 - Present)
- Conducted data collection, processing, and analysis for novel study evaluating the impact of over 300 biometrics variables on human performance in hyper-realistic, live-fire training scenarios
- Applied unsupervised deep learning approaches to longitudinal ICU data to discover novel sepsis sub-phenotypes
Projects
Ames Weather Data ETL Pipeline
I used the Open-Meteo API to collect Ames, Iowa weather data from March to April 2024 and built a serverless ETL pipeline using Python, SQL, and AWS tools like Lambda, Kinesis Firehose, and Glue. This enabled me to transform real-time data and create insightful dashboards in Grafana.
Global Layoffs: Data Cleaning with SQL
In this project, I used SQL to clean and prepare a dataset on global layoffs between 2020 and 2023 for exploratory data analysis (EDA). The primary goal was to transform raw data into a clean, standardized format suitable for in-depth analysis.
Global Layoffs: An EDA with SQL and Tableau
In this project, I conducted an exploratory data analysis on layoff trends from 2020 to 2023, using SQL to query and analyze the data, and Tableau to visualize key insights such as industry impacts and geographical distribution. I focused on identifying patterns and significant factors contributing to layoffs
Data Cleaning in MS Excel
In this project, I used MS Excel to clean and organize a dataset by applying various data cleaning techniques, such as removing duplicates, correcting formatting, and splitting columns. By leveraging Excel’s built-in functions and tools, I transformed the raw data into a structured format ready for accurate analysis.
