Data Analyst Python

Maryam Amirizaniani

******.************@*******.** • https://www.linkedin.com/in/amirizaniani/ • +1-647-***-****

Skills

Programming Python • Pytorch • Tensorflow • R • SQL • MongoDB • VBA Software Power BI • Tableau • IBM SPSS

Familiar With C/C++ • PHP • HTML • CSS • Bootstrap Pascal Other Skills Microsoft Office (Word • Excel • PowerPoint • Access • Visio) Soft Skills Leadership • Detail-oriented • Problem-solver • Team-worker • Fast- learner

Notable Projects

Mar 2021 Sentiment analysis of blockchain with Machine learning & Deep learning. predicted people’s attitude about blockchain technology by machine learning and deep learning models. Also, blockchain in different industries was analyzed. Technologies Used: SVM, GLM, LSTM, CNN, Ensemble Model, TF-IDF, SQL. Feb 2021 Comorbidity analysis of brain disorders by Machine learning & Deep learning. Developed machine learning & deep learning models for the comorbid analysis of ASD, ADHD, and ID disorders and predict the future of these disorders. Some diseases which are associated with these disorders recognized.

Technologies Used: Logistic Regression, GLM, CNN, KNN, SVM, MLP, SQL, GCP. Dec 2020 Future of Alexa.

Used sentiment analysis to predict the future of Alexa in different filed like business, start-ups, management, parenting and etc. To apply this prediction, some machine learning and deep learning models are hired and evaluated.

Technologies Used: SVM, GLM, LSTM, CNN, LSTM+CNN, TF-IDF, Word2Vec, SQL. Oct 2020 Female Canadian Entrepreneurs.

Proved a gender gap in Canadian Entrepreneurs with data analysis on a big data. By help of machine learning models potential reasons revealed. Technologies Used: Simple LR, Logistic Regression, GLM, CNN, Tableau, Python, Power BI, SPSS. Apr 2020 Customer recognition at InnScience.

Used Python, SQL, and Google Analytics to analyze datasets and find the most profitable parts of the start-up. The goal of this project was customer activity recognition. Technologies Used: Python, SQL, Google Analytics

Apr 2019 Cheese Factory.

Applied a data analysis on datasets of a cheese factory. The result showed the profits of the company, popular cheese types, most popular locations, products with highest complaints, sales in each years and quarters, and etc. Some of this information provided in a dashboard. Also, some sales forecasting on their products was applied. Technologies Used: GLM, Python, SQL, Tableau, Power BI, Descriptive Analysis, SPSS.

Experiences

Sep 2019 - Present Research Assistant, Ryerson University, Toronto, ON, CA: Cleansing big data and prepare that for applying quantitative and quantitative analysis on that. Also, developing machine learning and deep learning models by Python, TensorFlow, and Pytorch to predict the future of dataset and provide some valuable information about datasets. Apr 2020 – Aug 2020 Data Analyst Intern, InnScienec, Toronto, ON, CA: (Contract) Used descriptive analysis and machine learning methods to recognize and predict customer activity. I used different libraryies of python like pandas, numpy, scikit-learn, scipy, matplotlib, seaborn, pytorch, Tensorflow. The result helped the start-up to provide products which customers are more interested in them.

Sep 2019 - Present Teacher Assistant, Ryerson University, Toronto, ON, CA: Experienced teaching and leadership as a teacher in courses such as Business Intelligence and Analytics (Teaching R), Enterprise Architecture (Teaching SAS), and Business Information System (Teaching Excel).

Jun 2019 - Sep 2019 Database Coordinator, IWOO, Toronto, ON, CA: (Contract) Analyzed data by python and SQL to derive insights and interpretation, leveraging findings to draw conclusions, and inform managerial action. Also, Predicted the future sales of the organization by machine learning models.

Jan 2019 - Jun 2019 Business Analyst Intern, Three Point Turn, Toronto, ON, CA: Cleansed and filtered data from multiple sources by python and SQL. Created dashboard by power BI to simply analyze organisation activity. Then, applied machine learning models to analyze the customers’ behaviour.

Dec 2013 - Nov 2018 Data Analyst, Shiraz Takhfif, Shiraz, Fars, IR: Enhanced data collection procedures to include relevant information, processing, cleansing, and verifying the integrity of data used for analysis. Analyzed clients' engagements and improvements by SQL and python.

Education

Sep 2019 – Apr 2021 MSc in Management (Information Technology Management). GPA: 4.12/ 4.33 Ryerson University, Toronto, ON, CA.

Aug 2012 – Jan 2015 MSc in Information Technology (Software design and production). GPA: 17.91 / 20 Islamic Azad University of Kerman, Kerman, IR.

Aug 2008 – May 2012 BSc in Information Technology. GPA: 15.15 / 20 Payame Noor University of Sarvestan, Fars, IR.

Certificates

In progress Reinforcement Learning

Jan 2021 Master in Python • Coursera

Aug 2020 R • TRSM Bootcamp

May 2020 Master in Python. • LinkedIn

Feb 2020 Mongo DB. • LinkedIn

Sep 2019 Statistics 101. • IBM, Cognitive Class

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