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VP of Data Science, Co-Founder of Deckard
Data Scientist & Machine Learning leader with more than 15 years experience evangelising and mentoring team mates in Deep Computer Vision, Geo-spatial and time series analysis, and NLP. AWS Glue/Athena/S3, Spark, Pandas, SOLR Lucene, Javascript/Flask/React & PostgreSQL/Oracle. Specialties: Machine learning & data exploration with AWS EMR, PySpark, SKLearn & R, Data visualization and wrangling in D3, Tableau and ELK, time series analysis with SARIMAX models, and model containment and deployment using modeldb and Docker. My thesis focussed on "Prediction of Crime rates using Big (Twitter) Data", employing big data techniques and spark/geospatial analysis. Masters of Data Science (completed 2018) - Academic Honour Roll two years running for first place in "Machine Learning" and "Statistical Natural Language Processing"
University of Sydney
Masters of Data Science, Machine Learning and Data Visualization
January 1, 2016 – January 1, 2019
The University of Queensland
BENG/IT, Computer Systems Engineering (1st class honours)
January 1, 2001 – January 1, 2006
Deckard Technologies
VP of Data Science, Co-Founder
June 1, 2018 – Present
Sydney, New South Wales, Australia
Qualcomm
Senior Staff Machine Learning Engineer
September 1, 2015 – May 1, 2018
Sydney, Australia
Qualcomm
Senior Staff Engineer
May 1, 2010 – September 1, 2015
Sydney, Australia
Canon Information Systems Research Australia (CISRA)
Software Engineer
January 1, 2007 – May 1, 2010
University of Queensland
Engineering Tutor
February 1, 2006 – June 1, 2006
iPower
Intern Software Engineer
November 1, 2005 – February 1, 2006
Citect
Intern Software/SCADA Engineer
December 1, 2004 – February 1, 2005
Edmund Rice Camps
Volunteer Leader
January 1, 2002 – July 1, 2009
Cultural Fit Analysis
The candidate's diverse experience across various companies (Deckard Technologies, Qualcomm, Canon, iPower, Citect) and roles (VP, Senior Staff Engineer, Software Engineer, Tutor, Volunteer) indicates adaptability and a broad perspective. Their involvement in volunteer work (Edmund Rice Camps) highlights a commitment to community and teamwork. However, the primary focus of their career has been in data science and machine learning, which is a significant pivot from a dedicated Quality Assurance role. While their engineering background provides a foundation, the direct cultural fit for a QA-centric organization without recent, explicit QA experience might require further assessment.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, teamwork, and communication skills through their roles as VP of Data Science, Senior Staff Engineer, and volunteer work. Their experience in coaching and mentoring (Engineering Tutor) also indicates good interpersonal skills. The operational fit for a Quality Assurance Engineer role is not directly evident from their primary experience in data science and machine learning, but their engineering background and focus on best practices (Docker, Jenkins, Github, Jira) suggest an understanding of robust development and testing principles.