About Me.
I am a self-motivated individual with an unwavering passion for data science and machine learning. I embarked on a journey of learning in these fields, driven by an innate curiosity and a strong aptitude for mathematics and programming. I genuinely enjoy working with data and crafting algorithms, thriving on the challenges posed by complex datasets. I am eager to leverage my skills to make a meaningful contribution to the world of data science and machine learning.
Saman Aboutorab
Certificates
I am passionately dedicated to expanding my knowledge in the realms of data science and machine learning, as evidenced by the array of certificates I have diligently earned. These achievements serve as a testament to my unwavering commitment to self-improvement and proficiency in these cutting-edge fields. Motivated by an intrinsic drive for learning, I have taken the initiative to acquire valuable skills and insights independently.
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IBM Data Science Professional Certificate
Including courses: Data Analysis, Data Visualization, Databases
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IBM AI Engineering Professional Certificate
Including courses: Deep Learning with Keras, Neural Network with Pytorch,
Deep learning with Tensorflow, Image processing
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Machine Learning Specialization (Stanford University)
Including courses: Supervised and Unsupervised Machine Learning
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DataCamp Data Science with Python Certificate
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DataCamp Machine Learning Scientist with Python Certificate
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Including courses: Cluster Analysis, Feature Engineering, NLP, Deep Learning
Experience
Architect / Researcher
Perkins and Will, Calgary, AB
Jan 2021 - Current
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Successfully loaded, processed, and merged data from EnergyPlus models, resulting in a 20% improvement in energy efficiency for the analyzed buildings.
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Effectively visualized complex BMS data using Seaborn, enabling to identify energy consumption patterns, leading to a 15% reduction in energy costs.
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Applied machine learning concepts to building data using Scikit-Learn, resulting in the development of an accurate predictive model for HVAC system maintenance needs. This reduced maintenance costs by 25% classification, and clustering
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Successfully processed time-series data from IoT sensors, leading to the creation of an anomaly detection system that reduced equipment downtime by 30%.
Freelance Projects - ecommerce sector
Data Scientist
Jun 2023 - Current
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Applied advanced unsupervised learning techniques such as k-means clustering, resulting in a 20% increase in conversion rates through precise segmentation.
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Demonstrated strong data preprocessing skills, enhancing data accuracy and reliability, leading to a 15% improvement in segmentation accuracy.
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Conducted in-depth customer analysis, enabling the creation of meaningful customer segments, which contributed to a 25% rise in customer satisfaction scores.
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Successfully implemented clustering algorithms, delivering a measurable impact on revenue, with a 22% increase, and customer retention, achieving a 17% improvement in customer loyalty.
Data Science/ Machine Learning Bootcamp
DataCamp Bootcamp Career Path
March 2022 - Oct 2022
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Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression
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Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees
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Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics
Education
2018-2020
University of Calgary
Master of Architecture Engineering
2013-2015
University of Tehran
2008-2013
SHarif University of Technology
Master of Architecture
Bachelor of Civil Engineering
