Agile Data Science (2.0!)


Join us after work from 5:30 for a beer and pizza.

Help yourself to pizza, and if you see the pizza man outside please give him a hand carrying them in. There should be plates and serviettes floating around.

Please assist in keeping the venue tidy during the evening - please put you empty drinks bottles in the the bin, and if you see any empty pizza boxes just stack them up.

Talks will commence at 6pm and be 20 mins each with a joint Q&A at the end.

Vaenthan Thiru: An Intro to Agile Data Science

Agile methodology is a flexible approach to software development where Stakeholders are closely coupled with the development process, and requirements and solutions are regularly re-assessed, thus reducing the chance of failure. We have seen a push for this philosophy to be applied to Data Science in recent times, presenting a new set of challenges. In this talk, Vader will cover the basics of Agile development, and highlight a few of the pitfalls within the realm of Data Science.

Vaenthan ‘Vader’ Thiru holds a PhD in Computer Science (Machine Learning) and has over 10 years of experience working in IT across several domains. He has worked in roles ranging from mobile system architecture, through to lecturing on databases at Charles Sturt University. At Servian, Vader has delivered excellence in projects at a number of clients, involving predictive modelling, prescriptive analytics, customer segmentation, statistical analyses and business intelligence.

Eric Wei : Agile Data Science 2.0: Some emerging best practices, personal experience and thoughts

A successful data science team requires a blend of different talents, a modern platform infrastructure foundation, and a robust solution development framework. There are fundamental challenges when teams are applying Agile development method directly to data science projects. In this talk Eric will take you through some emerging best practices for leading data science teams with a focus on achieving agility and speed to value.

Eric Wei is a data science manager in Accenture’s Applied Intelligence group. In his current role Eric’s key responsibilities include team capability development, leading client data science engagements, as well as developing go-to-market strategies for Accenture’s data science and artificial intelligence offerings. Prior to Accenture Eric was a lead data scientist for Hewlett Packard Enterprise in the Asia-Pacific region.

Felipe Flores: Agile Data Science in the wild!

Due to their complexity, large corporate environments create a number of constraints which make it difficult to completely apply the agile principles described in the theory. This leads to several mistakes and myths in their application. Does that mean agile principles are of no help or that they shouldn't be applied? Not at all! In this talk we'll find out about some of the compromises that need to be made when applying agile data science in the wild effectively.

Felipe Flores is a data science leader and entrepreneur who has been applying data science in large organisations and complex environments for 15 years. He worked in consulting for 7 years, then his own analytics consulting company which he led for 5 years. He had a successful exit and later became the Head of Data Science at ANZ Institutional for 3 years. He's led data science teams of up to 50 people applying agile principles in all their projects.