My resume

work experience

2018 - Now

SAS Institute – Current

From March 2018 to present day

Domain Leads Manager - Analytics Platform

As the domain leads manager for SAS Australia/New Zealand, I lead a team of talented and passionate product domain leads who help organisations solve some of the most complex business problems. We offer advice and solutions across multiple disciplines across the analytics spectrum including data management, BI/Data Visualisation and advanced analytics/machine learning.

2016 - 2018

SAS Institute – BSM (BI and Big Data Analytics)

2016 - March 2018

Business Solution Manager - Business Intelligence & Big Data Analytics

As the business solution manager for SAS Australia/New Zealand, I was responsible for driving the growth of SAS Data Visualisation and Big Data Analytics solutions. This includes Business Intelligence/Dashboard solutions, next generation Data Visualisation solutions as well as big data analytics solutions targeted at citizen data scientists.

I have primary responsibility for field sales operation as well as design and deployment of marketing campaigns and initiatives within the ANZ region.

2010 - 2016

SAS Institute – BSM (IM and Big Data)

2010 - March 2016

Business Solution Manager - Information Management and Big Data

I was the business solution manager for SAS Australia/New Zealand, responsible for driving SAS Information Management and Big Data solutions. This includes traditional data management solutions, data streaming solutions as well as Hadoop specific big data solutions.

I have primary responsibility for field sales operation as well as design and deployment of marketing campaigns and initiatives within the ANZ region.

Key Achievements:
- Successfully launched the SAS Visual Analytics offering in Australia (160% growth in BI in 2013)
- Established SAS MDM solution presence n Australia with 100% revenue growth from 2012 to 2014
- Successfully managed the execution of large scale marketing product workshops (7 cities, 300+ attendees)
- Featured thought leader and blogger on SAS.com
- Speaking engagements at industry conferences, partner events and guest lecturing at major Australian universities

2005 - 2010

IBM

from November 2008 to March 2009

Senior Product Specialist

IBM-logo1Provide technical sales leadership within the ANZ IBM InfoSphere software group. Successfully drove significant revenue growth in IBM data management solutions including DataStage, QualityStage, Information Server and MDM Server.

Key Achievements:
- Exceeded sales revenue target and made IBM high achievers club within the first two years consecutively
- Instrumental in building and enabling key new business partners (4 new system integrator partners in 2 years) that resulted in new account engagements and overall revenue increase through the partner channels

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2004 - 2005

HP (Autonomy)

from August 2004 to November 2005

Solution Specialist

hp-logo-480x480Provided technical sales leadership for the ANZ team. Responsible for supporting channel partner program and direct sales of Autonomy Enterprise Search Solution in the Australia/NZ region.

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2003 - 2004

TIBCO

from May 2003 to August 2004

Solutions Consultant

tibco_logo-2xImplementation and deployment support for the Tibco Staffware workflow solution.

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Education experience

2007 - 2009

Macquarie Graduate School of Management (MGSM)

from 2007 to 2009

Master of Business Administration (MBA)

macquarie-graduate-school-of-managementMajored in Strategy/Finance and graduated with distinction average.

Certificate of Merit Award for outstanding achievement in Accounting (High Distinction)

Electives included:
- Law and Management
- Business Performance Measurement
- Insolvency and Restructuring
- Strategic Management

1996 - 1999

University of New South Wales

from 1996 to 1999

Bachelor of Engineering (Computers Engineering)

UNSWFinal year electives included:

- Human Computer Interaction
- Image Processing and Applications
- Object-Oriented Software Development
- Total Quality Management

2014 - 2016

Coursera Data Science Specialisation

From 2014 to 2016

Data Science Specialization

JHU-Logo-Square-Mini_180px This specialization created by Johns Hopkins University covers the concepts and tools needed throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Courses included and completed:

- The Data Scientist’s Toolbox
- R Programming
- Getting and Cleaning Data
- Exploratory Data Analysis
- Reproducible Research
- Statistical Inference
- Regression Models
- Practical Machine Learning
- Developing Data Products
- Data Science Capstone Project

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2016

SAS Certified Big Data Professional

2016

SAS_certifiedSAS Certified Big Data Professionals have demonstrated the ability to use open source and SAS data management tools to prepare big data for statistical analysis and are skilled in such tasks as recognizing and overcoming big data challenges, accessing, transforming, and manipulating data, applying fundamental statistical techniques, working with SAS, Hadoop, and Hive, and exploring and visualizing data.

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2017

SAS Certified Advanced Analytics Professional

2017

SAS Certified Advanced Analytics Professionals have demonstrated the ability to analyze big data with a variety of statistical analysis, machine learning, optimization, and predictive modeling techniques.

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2017

SAS Certified Visual Modeler Using SAS Visual Statistics 7.4

2017

SAS Certified Visual Modelers have demonstrated the ability to build and explore predictive and descriptive models, assess models, compare models and score models using SAS Visual Statistics.

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2017

SAS Certified Data Scientist

2017

SAS Certified Data Scientists have earned the SAS Certified Big Data Professional and the SAS Certified Advanced Analytics Professional Using SAS 9 credentials.  These individuals have demonstrated the ability to manipulate and gain insights from big data with a variety of SAS and open source tools, make business recommendations with complex machine learning models, and then deploy models at scale using the flexible, robust SAS environment.

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Endorsements