Saeed Pouryazdian
Data AnalystMachine Learning Specialist | MLOps
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Specialist | MLOps
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Saeed is an experienced data science practitioner with deep knowledge in the application development lifecycle, machine learning (MLOps), data engineering, and analytics strategy within a customer analytics function. He is passionate about data and working with high-performance analytics teams, and applying innovative approaches using ML to drive business impact. - Expert in problem-solving and programming in Python, R, and Spark. - Some codes on my GitHub: https://github.com/saeedp62
Ryerson University
Doctor of Philosophy (Ph.D.), Electrical Engineering
January 1, 2011 – January 1, 2016
Iran University of Science and Technology
Master of Science (M.Sc.), Biomedical/Medical Engineering - Bioelectric
January 1, 2006 – January 1, 2009
Ferdowsi University of Mashhad
Bachelor of Science (B.Sc.), Electrical, Electronic and Communications Engineering
January 1, 2001 – January 1, 2006
theScore
Senior Machine Learning Engineer - MLOps
July 1, 2024 – Present
Toronto, Ontario, Canada · Hybrid
Invafresh
Senior Data Scientist - MLOps
June 1, 2021 – June 1, 2024
Mississauga, Ontario, Canada · Hybrid
Manulife
Data Scientist
January 1, 2019 – May 1, 2021
Toronto, Canada Area
Manulife
Machine Learning Developer
December 1, 2018 – January 1, 2019
Toronto, Canada Area
TELUS
Software Developer - Machine Learning (Contractor)
August 1, 2016 – December 1, 2018
Scarborough, ON
Ryerson University
Research Assistant
January 1, 2011 – June 1, 2016
Toronto, Canada Area
Takeen
Software Engineer
September 1, 2009 – August 1, 2010
Iran · On-site
Iran Neural Technology Center
Research Assistant
August 1, 2007 – August 1, 2009
Iran
SSVEP-based Brain-Computer Interface
June 1, 2007 – September 1, 2009
• Steady-State Visual Evoked Potentials (SSVEP) used as the input of the BCI. • Visual stimulation system was programmed on ATmega128 microcontroller. • Acquiring EEG signals from subjects and analyzing them. • Real-time multi-Channel EEG signal processing and feature extraction. • A new method for event detection based on Principle Component Analysis (PCI) and high order statistics (HOS) was proposed. • Data cleaning and classification. • The results are published in two conference papers.
Data Science Specialization
Coursera Course Certificates
June 24, 2026 – Present
Practical Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Regression Models
Coursera Course Certificates
June 24, 2026 – Present
Getting and Cleaning Data
Coursera Course Certificates
June 24, 2026 – Present
R Programming
Coursera Course Certificates
June 24, 2026 – Present
Data Science Capstone
Coursera Course Certificates
June 24, 2026 – Present
Developing Data Products
Coursera Course Certificates
June 24, 2026 – Present
Statistical Inference
Coursera Course Certificates
June 24, 2026 – Present
Exploratory Data Analysis
Coursera Course Certificates
June 24, 2026 – Present
Reproducible Research
Coursera Course Certificates
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning academic research, software development, and senior data science/MLOps roles across various industries (telecommunications, finance, retail tech, sports tech). This breadth of experience suggests adaptability and a willingness to tackle different challenges. However, the target role is 'Data Analyst', while the candidate's recent roles are 'Senior Machine Learning Engineer' and 'Senior Data Scientist - MLOps'. While the skills are highly transferable, the role title might indicate a slight mismatch in career trajectory or a potential overqualification for a pure 'Data Analyst' role, which could impact long-term cultural fit if the role doesn't offer sufficient advanced analytical or ML opportunities.
Soft Skills & Operational Fit
The candidate's experience includes collaborating with product managers and business analysts, presenting deliverables to both technical and business stakeholders, and coaching junior developers. This suggests strong communication, collaboration, and mentorship skills, which are crucial for operational fit in a senior role. The academic background and research experience also point to strong problem-solving and analytical thinking.