titanium-cranium
Brendan O'Brien
Melbourne, Australia

Much of consulting is about knowing how to ask the right questions. Only after the problem space is well defined can we engineer the right solution. I spent my early career as a scientist learning how to ask the right questions. My research focussed on understanding how the brain decomposes and processes the visual world so we can make sense of it. The data we uncovered helped us to design, build and test the effectiveness of the Bionic Eye. Nowadays, I use my experience as a scientist to help clients ask the right questions, my understanding of data analysis to create valuable insights and my skill as a software engineer to build the right solution.

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List your work history, including any contracts or internships
DiUS
Apr 2021 - Feb 2022 (10 months)
Remote
Consultant
Engineering consultant doing various projects. Currently working in fintech building microfrontends and cloud uplift.
python ReactJS terraform pydantic pytest aws docker compose docker
Envato
Sep 2018 - Mar 2021 (2 years 6 months)
Remote
Engineer
Internationalisation of Envato Elements

As part of the i18n team, I helped construct two Ruby on Rails apis using an event sourced approach. The Translation Bot API watched all github merges to master and extracted any new or changed frontend copy to the site and forwarded these to the Translation Service. The Translation Service API received requests and forwarded them onto external services for either human (frontend copy) or machine (item titles/descriptions) translations. Completed translations were made available for consumption on the event feed.

Tech Stack: Ruby/Rails, RSpec, Postgresql, Heroku, Buildkite, AWS Translate, Datadog, SumoLogic


Conversion Funnel Improvements.

Using Hypothesis Driven Design, we improved conversion on Envato Elements by over 40%. Our cross-functional Agile team worked together to propose hypotheses, design, engineer and analyse the results of user behavioural data acquired via Google Analytics/Optimize. Results were used to confirm or reject the experimental changes and used to inform the next round of improvements.

Tech Stack: ReactJS, Node, Cypress, Jest, Google Analytics & Optimize
ruby on rails ReactJS python airflow aws sumo
Factil
Dec 2017 - Aug 2018 (8 months)
Melbourne, Australia
Data Scientist/ Software Engineer
Interstate Child Protection Data Matching

After the Royal Commission into Child Abuse Factil was contracted by the Federal Government to produce a means for collaboration among state child protection systems whilst maintaining individual privacy. We used Machine Learning to identify matching records in child protection data across states combined with Feature Engineering to define the parameters. Case workers were then notified that additional interstate data was available.

Tech Stack: Python, Jupyter Notebooks, SciKit-learn, Seaborn, Ruby/Rails, Postgresql, SQL
Machine learning Python jupyter notebook jupyter notebook scikit learn pandas numpy tensorflow data science data visualization postgresql

Add some compelling projects here to demonstrate your experience
Robot Combat Events
Nov 2016 - Present
Titanium Cranium Enterprises
A two sided marketplace for organizers to create events for robot builders to register to compete. It uses Stripe to handle electronic registration fee transactions.
ruby on rails rspec stripe heroku aws challonge postgresql
Academic Career
Jun 1991 - Jul 2013
Various
As an academic my main focus was in visual neuroscience studying at all levels, from gene expression, electrophysiology, neuroanatomy, bioengineering to behaviour. I worked in top tier Universities around the world and published in high impact journals.
This section lets you add any degrees or diplomas you have earned.
University of Washington
Doctor of Philosophy (PhD), Neuroscience
Jan 1991 - Jan 1997
Began a career investigating the anatomy, physiology and molecular genetics of the mammalian visual system.
Optimize ML Models and Deploy Human-in-the-Loop Pipelines
Sep 2021
Practical Data Science Specialization
Sep 2021
Build, Train, and Deploy ML Pipelines using BERT
Aug 2021

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