Software Engineer, ML & Algorithms
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Assessing your cultural and operational fit
Machine learning and algorithmic design engineer helping small and large organizations build intelligent tools. Background in physics and computer science. Authorized to work in the US and Canada.
Coursera
Machine Learning
January 1, 2015 – Present
McGill University
Bachelor of Science (B.Sc.), Physics & Computer Science
January 1, 2013 – January 1, 2017
Software Engineer, ML & Algorithms
Software Engineer, ML & Algorithms
October 1, 2018 – Present
New York, United States
Lean Systems (Techstars NYC '17)
Software Engineer - Machine Learning & Algorithms
June 1, 2017 – October 1, 2018
New York City Metropolitan Area
McGill University
Undergraduate Research Assistant at THz Spectroscopy Lab
January 1, 2017 – April 1, 2017
Fier Consulting
Founder, Technical & AI Lead
September 1, 2016 – June 1, 2017
Greater Montreal Metropolitan Area
WealthTab
Data Science & Machine Learning Intern
June 1, 2016 – August 1, 2016
Montreal, QC
McGill University
Director of Private Pilot Ground School Operations
November 1, 2015 – March 1, 2017
Oceanwide
Software Developer Intern
May 1, 2015 – August 1, 2015
Greater Montreal Metropolitan Area
McGill University
Undergraduate Research Assistant
April 1, 2015 – November 1, 2015
Intelliberg Associates
Assistant to CEO
September 1, 2013 – August 1, 2015
Eagleville, PA, USA
Philadelphia Insurance Companies
Human Resources Intern
June 1, 2011 – August 1, 2011
Bala Cynwyd, PA, USA
Virtual File & Memory Allocation Systems
November 1, 2015 – Present
- Implemented a simple UNIX-like file system (C) with a multi-level indexing block allocation scheme, supported by FUSE kernel module - Built robust malloc implementation supporting first-fit and best-fit allocation schemes
Experimental Data Analysis in Physics Laboratory
September 1, 2015 – Present
- Use MATLAB to process data, build statistical models, and produce visualizations from measurements obtained in physical experiments on a variety of topics
Co-Founder & R&D Team Member, McGill Hyperloop Design Team
July 1, 2015 – Present
- Conducting R&D in the overarching design and key safety systems of half-scale Hyperloop pod as well as subsystem feasibility and integration (Simulink) - Designed novel air ski levitation and lateral control system to operate in low-pressure environment at sub-and transonic speeds, including model building (AutoCad) and part design - Led team in outreach and marketing by direct contact and social media to obtain sponsorships from University and corporate groups - Recruiting and onboarding of new team members
Search Engine Algorithm
November 1, 2014 – Present
- Developed algorithm incorporating graph search and pagerank scheme (Java) for a segment of the internet for an individual class project.
Mock Store Website
November 1, 2014 – December 1, 2014
- Successfully co-developed and integrated a mock online store selling luxury vehicles within a team-based class project. - Developed front and back ends of catalogue page using (Python, CGI, HTML).
Virtual CPU
November 1, 2014 – December 1, 2014
- Co-developed virtual pseudo-pipeline CPU architecture using Logisim within a team-based class project. - Led development of control unit, tailored micro-instruction set, execution code, and total project documentation.
RoboElectronics Club Competition
September 1, 2014 – November 1, 2014
- Developed control system and integrate sensor data for small self-parking robot with balancing capabilities. - Soldered and integrated electrical and hardware components, including microcontroller and infrared sensors, to build robot from scratch.
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from low-level systems (file systems, virtual CPU) to high-level applications (ML for finance, logistics), indicates a broad technical curiosity and adaptability. Their involvement in a Hyperloop design team and various research assistant roles suggests a proactive, innovative, and team-oriented mindset. The transition from physics to computer science and then specializing in ML demonstrates a strong learning agility. While the target role is 'Data Analyst', the candidate's experience leans heavily towards 'Data Scientist' or 'Machine Learning Engineer', which might indicate a slight mismatch in the depth of analytical work versus the breadth of data analysis typically expected for a pure analyst role. However, their foundational data analysis skills are strong.
Soft Skills & Operational Fit
The candidate's experience as a co-founder and R&D team member, along with roles involving client interaction and team leadership, suggests strong communication, collaboration, and problem-solving skills. Their work in designing user interfaces and interfacing with industry specialists indicates an ability to translate technical concepts into practical solutions and work effectively with diverse stakeholders. The project descriptions are clear and concise, indicating good written communication.