Python Engineer

Alireza Tajadod Email : adc0f7@r.postjobfree.com

https://github.com/ATajadod94 Mobile : +1-416-***-****

Experience

VividSeats Toronto, Ontario

Software Engineer Oct 2019 - Present

Marketplace - B2B: The Marketplace API is the core of Vividseats B2B services. I use Django, Flask, Vue, Albemic, Vagrant, ansible and SQL to develop multiple new features and on board new partners via test driven and Agile environment.

fanx-tests-automation: The fanx test automation is a project to automate regression testing for all frontend aspects of the B2B side of vividseats. I used Python to work with the Quality Engineering team to redesign, test and develop a new framework for testing new, existing and future features and partners

Facebook-API: The Facebook API is a B2B project designed from scratch to enable VividSeats upcoming partnership with Facebook. I used FastAPI and Docker to design and develop the platform from scratch.

ScotiaBank Toronto, Ontario

Credit Risk Developer Feb 2019 - Sep 2019

AlgoX: AlgoX is a counterparty credit risk reporting application based on IBM’s Algo application for enterprise. I use Django, PostgreSQL, Docker and Jenkins to deliver multiple new reports and features via test driven development.

Robotframework: Robotframework is a python based framework for automated testing. I used Python, PostgreSQL and Oracle database to develop an external library for processing and importing various trade feeds to various SQL libraries. This delivery also included SQL scripts which automate previously manual QA jobs.

CORA: Cora is the credit overruns resolution application at Scotiabank. I worked with Flask, Django, PostgreSQL, Docker and front end technologies to integrate CORA into the existing AlgoX platform. This project included optimizing the application, specially SQL queries, to maintain performance despite the increase in data size.

Rotman Research Institute Toronto, Ontario

Research Analyst Jan 2017 - Feb 2019

ALITrack: I used Matlab to create a package to read, preprocess, visualize and automate analysis of eye-movement data. This helped automate a task which was previously done manually through a third-party software.

The Virtual Brain client: I used Python to develop a package for using The Virtual brain. Subsequently, I used this package to perform network-wide brain generative modeling. This package helped create more research exibility with the TVB’s API in our lab.

Brain Connectivity: I used Bash, Matlab, Python, and machine learning techniques to preprocess, analyze and predict brain activation patterns and functional connectivity based on brain functional imaging data

Sensorimotor Control Lab York University

Lab programmer/ Technician Jun 2016 - Jan 2017

Pyselector: I used Python and wxwidgets to develop a graphical user interface for preprocessing, visualizing and basic analysis of hand movement data. This helped speed up the preprocessing of data by the lab’s volunteers.

Experiment design: I used Matlab, Python, and TCL to code dozens of scienti c experiments for published or soon to be published papers. I improved the data collection performance and real-time data analysis from previous experiments.

Maintenance work: One of my key responsibilities was to maintain and improve on legacy code from various experiments and programs.

Certificates

Scrum master Certi cate of mastery in Scum and Agile development

Deep learning specialization Deeplearning.AI Certi cation for Machine learning Education

Bachelor of Applied mathematics and Philosophy Toronto, ON York university Sep 2014 { June 2018

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