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AmirArsalan SaghriAS
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AmirArsalan Saghri

@amirarsalan

Statistics student passionate about data science and machine learning, with hands-on Python experience and a drive to solve real-world problems.

Iran
Message

I am a Statistics undergraduate at the University of Tabriz, interested in data science, applied machine learning, and using data to solve real-world problems. My academic background has introduced me to statistical analysis, hypothesis testing, regression analysis, and time series.

I have hands-on experience with Python and libraries such as pandas, NumPy, and scikit-learn through data analysis and machine learning mini projects, including working with datasets and building a model for the MNIST handwritten digit classification task. I am also developing ProjectSkill, a Python-based project focused on collecting job postings and analyzing job-market demand for technical skills.

My main career goal is to build strong practical skills at the intersection of statistics, data science, and software development. I am particularly interested in opportunities where I can work with real-world datasets, develop analytical solutions, and learn from experienced professionals.

I am currently seeking internship, trainee, or entry-level opportunities in data analytics and related fields where I can contribute, strengthen my technical abilities, and grow into a capable data professional.

Experience

Work history, roles, and key accomplishments

SA

Central Council Member

Statistics Students' Scientific Association

Jan 2024 - Jan 2025 (1 year)

Proposed and implemented a computer vision demonstration for a university science event, integrating DeepFace for real-time facial attribute analysis.

Education

Degrees, certifications, and relevant coursework

University of Tabriz logoUT

University of Tabriz

Bachelor of Science, Statistics

2023 -

Activities and societies: Central Council Member, Statistics Students' Scientific Association

Pursuing a Bachelor of Science in Statistics with a strong foundation in statistical analysis and practical experience using Python, pandas, NumPy, and scikit-learn.

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