Vincent Alexander Saulys

My Email: contactvincent@saulys.me

About Me

Currently living in New York City. Authorization to work anywhere in the United States and European Union.

I've worked in a professional capacity in C++, Python, and Javascript. I have extensive experience in Docker, cloud compute environments, microservices, and machine learning.

Interested in building software products that others use. That includes line-of-service internal software as well as applications touched by end users extenal to the company.

Love things that "just work", which means test - test - test to ensure robustness so one can deploy with confidence. That means having a tight feedback loop with stakeholders to ensure requirements are met, being able to move quickly so adjustments can be made, and working within sometimes vague and ambiguous constraints.

Love to move quickly, which means having a tight write - build - test loop. That includes using docker to tightly containerize an application. Doing so forces you to explicitly state your requirements and decouples you from whatever OS you originally built on. It also means

Never picky about technology. If its an old C++ application, I'll dust off the Strousoup book and get my hands dirty. Getting things done is what matters.

Strong belief in the importance of documentation. Others should know what you built and be able to pick up at a moment's notice without issue. Writing forces you to think through what you did and what you will do so you're not wasting time flailing in the wrong direction.

Work Experience

Senior Software Engineer, Bloomberg LP, Compliance Engine Systems Team.

January 2022 -- Current
  • Developing extensive test suite -- integration, end-to-end system, unit both in Docker and on bare metal -- for covering market value calculations used in AIM's Rules Compliance Engine.
  • Deployment of mission critical features for a multimillion dollar application that supports billions in trades daily.

Data Scientist, Bank of America, Equity Infrastructure Team

April 2019 - July 2021
  • Rewrote end-of-day regression tests for work in Parallel via a batch-job setup called Quartz that is custom to BoA.
  • Built "sonar" machine learning tools to identify performance problems, memory leaks, and database issues for the Quantative trading platform.
  • Worked closely with quants to optimize their distributed computing strategies across the whole of BoA's Quartz infrastructure. Automated QA processes.

Data Scientist & Machine Learning Engineer Zyper, Startup Team

August 2018 - January 2019
  • Built computer vision models from scratch using cutting edge neural networks in Tensorflow to identify worthy candidates for the Zyper marketing platform using scraped Instagram photos and profiles.
  • Identified blockers, communicated with product development team, integrated within the platform backend while accumulating minimal technical debt.
  • Developed ELT pipelines to extract data from myriad of sources, load them into a common database, then transformed into training data for models.

Data Scientist (Senior Associate), Bank of New York Mellon, Global Infrastructure Team

June 2017 - August 2018
  • Worked with distributed platforms team to stabilize Docker application deployments.
  • Built an early warning system for detecting when servers were to fall over before they actually did.
  • Developed investigative reports for C-level senior management on legacy hardware (~60k servers) remediation using vulnerability reports.

Education

Columbia University in the City of New York

Masters of Science in Applied Analytics, 2019

McGill University in Montreal, Quebec, Canada

Bachelor's of Engineering in Materials Science CO-OP, 2017

Deferred Exception

I maintain a personal blog and ocassionally write about different topics, mostly technology and finance.

Odds & Ends

Achieved the rank of Eagle Scout in 2012. Participated in a 50 mile trek through Philmont, New Mexico as part of my time with the Boy Scouts of America.

Lead the McGill University team in the inaugural Hyperloop Competition in 2015/16, which successfully submitted a design that was approved by SpaceX & Tesla engineers amongst ~40 participating teams.

Co-Op & Internship work before 2017

  • Research Assistant for PhD candidates at McGill University. Studied how electrical steels reacted under deformation.
  • Early software engineer for AON3D in Montreal, Quebec. Worked on interface software with the 3d printer firmware.
  • Deep Learning Intern for SensAuraTech. Studied and built deep learning models for identifying emotions based on physiological signals.