Enterprise Data Science Architecture Conference 2020

27th March 2020 at Melbourne Marriott Hotel, Melbourne Australia

Deploy Real Data Science Solutions at Enterprise Scale - Our industry moves fast. Don't get left behind.

Learn how leading enterprises deploy scalable data science solutions. Connect with leaders in this new field of data science architecture. Learn best practices and keep up with the latest innovations.

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The Enterprise Data Science Architecture Conference focuses on how to properly productionise data science solutions at scale. We have confirmed speakers from ANZ Bank, Coles Group, SEEK, ENGIE, Latitude Financial Services, Microsoft, AWS and Growing Data. The combination of presentations is intended to paint a complete picture of what it takes to productionise a profitable data science solution.

Our field flies fast. Keep your skills current.

As an industry, we are figuring out how to best build end-to-end machine learning solutions. The workflow starts with data sourcing, data preparation, feature engineering, building the machine learning model, testing the ML model, deploying to production, monitoring in production, getting feedback and then repeating the process with improved models and better features. Companies are currently learning how to build it all into one smooth pipeline. The presentations at our conference will show you what works today in leading enterprises. Reserve your place now, while tickets are still available.

Your toolkit for real projects.

Enterprise scale brings its own challenges and solutions. Automation, resilience, scalability and the appropriateness of the data science techniques used have significant impact on profit and loss. Governance is also important because of privacy laws and because large enterprises often operate in regulated industries. The presentations at our conference will focus on how enterprises are productionising machine learning solutions. We are still learning as an industry. Knowledge of best practices in end-to-end machine learning pipelines will become essential skills - demanded by clients and employers. Keep your skills current. Register today.

Where Data Science Architecture Fits

Our presentations will focus on how to properly deploy data science solutions in the enterprise. Enterprise solutions encompass the four broad categories below.

Infrastructure
Databases, Data Lakes, VMs, Kubernetes, Containers, Load Balancers, Virtual Networks, REST APIs, Dashboard Servers, Security, Availability, Resilience, Scalability
Data
Datasets, MLOps, Timeliness of Data, Feature Engineering, Transformations, Data Security, Encryption, Governance, Data Lineage, Data Pipelines
Methods
AutoML, Deep Learning, Reinforcement Learning, Recommender Systems, Supervised Learning, Unsupervised Learing, Charts, Dashboards, MLOps, AI, Statistics
Regulatory
Australian Privacy Principles, Responsible Gambling, Direct Marketing Code of Conduct, Medical Information, Security, Encryption, Governance

Speakers

Learn From Leaders

ANZ Bank

Jonathan Robinson

Principal Data Scientist @ ANZ Bank

Expand

Building a successful data science capability

Jonathan Robinson

Jonathan is a data scientist and engineer, leading analytics and data science for retail banking products and services for ANZ's Australian customers. He has previously worked at the Commonwealth Bank in the big data group, built data science platforms and capability at National Australia Bank and Suncorp and has several years experience researching and developing algorithmic systems for high frequency stock trading using machine learning for pattern recognition. He holds an MSc in physics from Otago University and a PhD in machine learning from Auckland university.

Coles Group

Richard Glew

Head of Data Engineering @ Coles Group

Expand

What does it take to build a great data platform?

Coles, like many organisations, has a data problem. We have some, we want a lot more, but it’s not easy. What can a large organisation with an established technology footprint do to radically transform the way it approaches data, making it available and good enough to use for all those fancy machine learning and analytics functions that businesses are demanding? Microsoft on the other hand, leverages data to continually transform its business, products and services and helps its customers undertake similar journeys. Richard and Ananth will talk about how Coles & Microsoft partnered to build Coles new data platform on Azure. They will explain the key problems that it is solving and the building blocks needed for successful delivery in an enterprise organisation. Hint - it’s not all about the technology!

Richard Glew

Richard has had a wide ranging career in technology, working in software engineering and data for more than 20 years throughout Australia, Europe and the United States. His background includes senior leadership roles at Disney, CTO of a digital education company, and prior to joining Coles, was a Principal Technologist at ThoughtWorks helping clients build cloud native platforms for systems and data. Now heading up Data Engineering and Operations at Coles, he is leading the retailer’s new data platform based on Azure. Richard holds a degree in Business Information Systems and is a certified Google Professional Cloud Architect.

Microsoft

Ananth Prakash

Lead Architect - Data, AI & IoT @ Microsoft

Expand

What does it take to build a great data platform?

Coles, like many organisations, has a data problem. We have some, we want a lot more, but it’s not easy. What can a large organisation with an established technology footprint do to radically transform the way it approaches data, making it available and good enough to use for all those fancy machine learning and analytics functions that businesses are demanding? Microsoft on the other hand, leverages data to continually transform its business, products and services and helps its customers undertake similar journeys. Richard and Ananth will talk about how Coles & Microsoft partnered to build Coles new data platform on Azure. They will explain the key problems that it is solving and the building blocks needed for successful delivery in an enterprise organisation. Hint - it’s not all about the technology!

Ananth Prakash

Ananth has a successful track record in delivery of strategic projects, products and platforms in the Data & AI domain for 16 years across North America, Australia and Asia. Some of his roles include leading product engineering groups at Oracle, Managing Consultant at IBM and Senior Technical Architect - Data & AI at Infosys. As a Lead Architect at Microsoft, Ananth helps enterprise customers architect & deploy strategic solutions on Azure to accelerate their business transformation journey.

Growing Data

Terence Siganakis

CEO @ Growing Data

Expand

Terence Siganakis

Terence Siganakis is the CEO of Growing Data, a Melbourne based consultancy providing services in Data Science, Data Engineering, Solution Architecture, Cloud Platforms, Data Strategy and Governance to companies such as ANZ and CSL and government agencies such as DHHS and PTV. Terence has a background in Computer Science and Bioinformatics as well as over 15 years experience in working with data in regulated industries.

Microsoft

Rolf Tesmer

Cloud Solution Architect - Azure | Data | Analytics | AI @ Microsoft

Expand

Operationalising ML model release using Azure DevOps

For the longest time data science was often performed in silos, using large scale compute operating across isolated copies of production data. This process was not repeatable, explainable or scalable and often introduced business and security risk. With modern enterprises now adopting a DevOps engineering culture, no longer can machine learning development practise operate in isolation of the business or existing applications teams. This demo heavy session introduces the new Azure ML Services capabilities and how this can assist to bring the practice of data science into the age of modern DevOps.

Rolf Tesmer

Rolf Tesmer works as a Azure Cloud Solution Architect (Data | Analytics | AI) for Microsoft Australia in Melbourne. He is certified Microsoft Solution Expert (MCSE) in Data Platform, Business Intelligence (BI) and Cloud Data Platform. He has been working with data platforms for over 20 years and has done just about everything around data related architectures since that time including Data Warehousing, Streaming Solutions / IoT, Machine Learning / AI, Visualisation and Spatial Data. He has had the opportunity to present at many industry events including PASS, Ignite, SQL Saturday, User Groups and Roadshows and really enjoys sharing and learning new ideas.

SEEK

Pramudi Suraweera

Principal Data Scientist @ SEEK

Expand

Building, deployment, and monitoring of models as containerised microservices with kubernetes

Pramudi Suraweera

Pramudi is a Principal Data Scientist at SEEK. He has been leading the development of AI services to help hirers post jobs and increase transparency between candidates and hirers. He has also been leading the modelling for SEEK’s new pricing initiative. His varied background includes leading an analytics team at Telstra within the direct marketing team, working at Deloitte as Senior Data Scientist, developing new machine learning algorithms as a Researcher at Monash University and developing models for teaching mathematics as a Cognitive Scientist at Carnegie Learning (USA). Pramudi holds an MSc in Computer Science and a PhD in AI for Education from the University of Canterbury.

ANZ

David Grice

Security Architect @ ANZ Bank

Expand

Protecting data…but from who?

A profile of the current state of data breaches, bad actors & attack types with guidance along the way on what you can do to address this in your organization.

David Grice

David works as an embedded security architect inside a data science and analytics team at ANZ. He guides and helps implement their overall security program by working closely with developers, ops & SRE on application and data security. David has a strong cyber security background in a range of roles amongst financial services and other highly regulated industries and has previously presented at a number of security conferences around Australia.

SEEK

Manuel Weiss

Tech Lead Personalisation Squad, AI Platform Services @ SEEK

Expand

Building global recommendation systems for local markets - The data challenges

Dr. Manuel Weiss

Manuel has been playing with computers since the early 90s, starting on MS-DOS and 640kB of RAM. He has studied a bit of Physics and has a degree in Computational Linguistics, as well as a PhD in Bioinformatics. He has worked in Zurich, London and Melbourne in a number of different companies and industries. Ranging from a media management system for police agencies to ad tech. He is currently the tech lead for the recommendations team at SEEK’s AI Platform Services department.

AWS

Julian Bright

Machine Learning Specialist @ AWS

Expand

From A to AI: Operationalising Machine Learning in 1 day

Companies are recognising the importance of cross-functional expertise in bringing AI-driven products to market, supported by efficient tooling. Just like DevOps helped organisations accelerate their software delivery schedules, in this session you will learn how to build an end-to-end pipeline for continuous delivery of Machine Learning models. By automating ML ops with Amazon SageMaker and serverless workflows you will be able to build, deploy & monitor models at scale to maximise the business value to your organisation.

Julian Bright

Julian has over 20 years’ experience building software and data science solutions in Australia and Europe from small start-ups to large multi-nationals. As a Machine Learning Specialist at AWS, Julian helps customers solve AI and ML problems by developing and deploying cloud native solutions at scale. Prior to AWS, Julian held senior positions as a Data Scientist and Architect as SEEK, where he applied machine learning and data engineering to develop recommendation and search algorithms to match candidates to hirers. Julian has won a number of hackathon events, is active in the Melbourne start-up community and has spoken at events including AWS Sydney Summit, Health 2.0, NDC and IJCAI.

SEEK

Tim Barber

Senior Engineer @ SEEK

Expand

Building, deployment, and monitoring of models as containerised microservices with kubernetes

Tim has been working in the Melbourne IT sector for nearly 20 years across a range of roles and different tech stacks. Currently a team leader at SEEK working alongside data scientists to help them deliver their models to production via Java microservices and Kubernetes.

SEEK

Amy Fitzgerald

Principal Engineer @ SEEK

Expand

Building Performant Cross Functional Teams

Cross functional teams are known for their high productivity and problem solving abilities. However, building and nurturing a cross functional team can be difficult. This talk will take a look at some successful strategies for building a functional, cohesive cross functional team.

Amy FitzGerald

Amy FitzGerald is a Principal Engineer on the AI Platform Services (AIPS) team in SEEK. Amy graduated from the National University of Ireland (NUIM) with a PhD in Computer Science and went on to work as a software developer in a range of companies including IBM, MasterCard and NAB. Amy is currently the tech lead of the Candidate Data Acquisition squad, a cross functional team within AIPS. Amy has a keen interest in creating and building performant teams.

ENGIE

Maya Muthuswamy

General Manager Analytics @ ENGIE

Expand

Real analytics in the wholesale electricity market

Maya Muthuswamy is the General Manager of Analytics at ENGIE Australia and New Zealand. She leads a team of problem-solvers to help the business solve complex and ambiguous problems, typically related to Australian wholesale electricity and gas markets. Maya has been leading this team since early 2017, and prior to this was the senior analyst in the team. Before joining ENGIE, Maya worked at AGL in load forecasting and commercial analysis. Maya's experience at AGL provided her with a solid grounding in the electricity and gas markets after finishing her PhD in 2008 at the University of Melbourne.

Latitude Financial Services

Shan Moorthy

GM of Architecture, Data & Engineering (CTO) (Acting) @ Latitude Financial Services

ANZ Bank

Anurag Soin

Director Data Science @ ANZ Bank

Expand

Anurag Soin

Anurag Soin is Director of data science at ANZ Institutional Banking where he works closely with clients to solve business problems leveraging data. Anurag is also actively engaged in the education sector as an advisory committee member of RMIT university and guest lecturer for the Master of Data Science program.

Anurag was recently recognised as top 25 analytics leader’s in Australia 2019 by IAPA for his work in the data science community. His most recent community engagement involves analysis of satellite image data to help predict impact on crop harvests.

More speakers will be announced as we get closer to the conference date...

Presentations

What you can learn at the conference

Real analytics in the wholesale electricity market

Maya Muthuswamy

Maya Muthuswamy - General Manager Analytics @ ENGIE

Maya Muthuswamy is the General Manager of Analytics at ENGIE Australia and New Zealand. She leads a team of problem-solvers to help the business solve complex and ambiguous problems, typically related to Australian wholesale electricity and gas markets. Maya has been leading this team since early 2017, and prior to this was the senior analyst in the team. Before joining ENGIE, Maya worked at AGL in load forecasting and commercial analysis. Maya's experience at AGL provided her with a solid grounding in the electricity and gas markets after finishing her PhD in 2008 at the University of Melbourne.

Building a successful data science capability

Jonathan Robinson

Jonathan Robinson - Principal Data Scientist @ ANZ Bank

Jonathan is a data scientist and engineer, leading analytics and data science for retail banking products and services for ANZ's Australian customers. He has previously worked at the Commonwealth Bank in the big data group, built data science platforms and capability at National Australia Bank and Suncorp and has several years experience researching and developing algorithmic systems for high frequency stock trading using machine learning for pattern recognition. He holds an MSc in physics from Otago University and a PhD in machine learning from Auckland university.

What does it take to build a great data platform?

Coles, like many organisations, has a data problem. We have some, we want a lot more, but it’s not easy. What can a large organisation with an established technology footprint do to radically transform the way it approaches data, making it available and good enough to use for all those fancy machine learning and analytics functions that businesses are demanding? Microsoft on the other hand, leverages data to continually transform its business, products and services and helps its customers undertake similar journeys. Richard and Ananth will talk about how Coles & Microsoft partnered to build Coles new data platform on Azure. They will explain the key problems that it is solving and the building blocks needed for successful delivery in an enterprise organisation. Hint - it’s not all about the technology!

Richard Glew

Richard Glew - Head of Data Engineering @ Coles Group

Richard has had a wide ranging career in technology, working in software engineering and data for more than 20 years throughout Australia, Europe and the United States. His background includes senior leadership roles at Disney, CTO of a digital education company, and prior to joining Coles, was a Principal Technologist at ThoughtWorks helping clients build cloud native platforms for systems and data. Now heading up Data Engineering and Operations at Coles, he is leading the retailer’s new data platform based on Azure. Richard holds a degree in Business Information Systems and is a certified Google Professional Cloud Architect.

Ananth Prakash

Ananth Prakash - Lead Architect - Data, AI & IoT @ Microsoft

Ananth has a successful track record in delivery of strategic projects, products and platforms in the Data & AI domain for 16 years across North America, Australia and Asia. Some of his roles include leading product engineering groups at Oracle, Managing Consultant at IBM and Senior Technical Architect - Data & AI at Infosys. As a Lead Architect at Microsoft, Ananth helps enterprise customers architect & deploy strategic solutions on Azure to accelerate their business transformation journey.

Building, deployment, and monitoring of models as containerised microservices with kubernetes

Pramudi Suraweera

Dr. Pramudi Suraweera - Principal Data Scientist @ SEEK

Pramudi is a Principal Data Scientist at SEEK. He has been leading the development of AI services to help hirers post jobs and increase transparency between candidates and hirers. He has also been leading the modelling for SEEK’s new pricing initiative. His varied background includes leading an analytics team at Telstra within the direct marketing team, working at Deloitte as Senior Data Scientist, developing new machine learning algorithms as a Researcher at Monash University and developing models for teaching mathematics as a Cognitive Scientist at Carnegie Learning (USA). Pramudi holds an MSc in Computer Science and a PhD in AI for Education from the University of Canterbury.

SEEK Logo

Tim Barber - Senior Engineer @ SEEK

Tim has been working in the Melbourne IT sector for nearly 20 years across a range of roles and different tech stacks. Currently a team leader at SEEK working alongside data scientists to help them deliver their models to production via Java microservices and Kubernetes.

Operationalising ML model release using Azure DevOps

For the longest time data science was often performed in silos, using large scale compute operating across isolated copies of production data. This process was not repeatable, explainable or scalable and often introduced business and security risk. With modern enterprises now adopting a DevOps engineering culture, no longer can machine learning development practise operate in isolation of the business or existing applications teams. This demo heavy session introduces the new Azure ML Services capabilities and how this can assist to bring the practice of data science into the age of modern DevOps.

Rolf Tesmer

Rolf Tesmer - Cloud Solution Architect - Azure | Data | Analytics | AI @ Microsoft

Rolf Tesmer works as a Azure Cloud Solution Architect (Data | Analytics | AI) for Microsoft Australia in Melbourne. He is certified Microsoft Solution Expert (MCSE) in Data Platform, Business Intelligence (BI) and Cloud Data Platform. He has been working with data platforms for over 20 years and has done just about everything around data related architectures since that time including Data Warehousing, Streaming Solutions / IoT, Machine Learning / AI, Visualisation and Spatial Data. He has had the opportunity to present at many industry events including PASS, Ignite, SQL Saturday, User Groups and Roadshows and really enjoys sharing and learning new ideas.

Building Performant Cross Functional Teams

Cross functional teams are known for their high productivity and problem solving abilities. However, building and nurturing a cross functional team can be difficult. This talk will take a look at some successful strategies for building a functional, cohesive cross functional team.

Amy FitzGerald

Amy Fitzgerald - Principal Engineer @ SEEK

Amy FitzGerald is a Principal Engineer on the AI Platform Services (AIPS) team in SEEK. Amy graduated from the National University of Ireland (NUIM) with a PhD in Computer Science and went on to work as a software developer in a range of companies including IBM, MasterCard and NAB. Amy is currently the tech lead of the Candidate Data Acquisition squad, a cross functional team within AIPS. Amy has a keen interest in creating and building performant teams.

From A to AI: Operationalising Machine Learning in 1 day

Companies are recognising the importance of cross-functional expertise in bringing AI-driven products to market, supported by efficient tooling. Just like DevOps helped organisations accelerate their software delivery schedules, in this session you will learn how to build an end-to-end pipeline for continuous delivery of Machine Learning models. By automating ML ops with Amazon SageMaker and serverless workflows you will be able to build, deploy & monitor models at scale to maximise the business value to your organisation.

Julian Bright

Julian Bright - Machine Learning Specialist @ AWS

Julian has over 20 years’ experience building software and data science solutions in Australia and Europe from small start-ups to large multi-nationals. As a Machine Learning Specialist at AWS, Julian helps customers solve AI and ML problems by developing and deploying cloud native solutions at scale. Prior to AWS, Julian held senior positions as a Data Scientist and Architect as SEEK, where he applied machine learning and data engineering to develop recommendation and search algorithms to match candidates to hirers. Julian has won a number of hackathon events, is active in the Melbourne start-up community and has spoken at events including AWS Sydney Summit, Health 2.0, NDC and IJCAI.

Building global recommendation systems for local markets - The data challenges

Dr. Manuel Weiss

Dr. Manuel Weiss - Tech Lead Personalisation Squad, AI Platform Services @ SEEK

Manuel has been playing with computers since the early 90s, starting on MS-DOS and 640kB of RAM. He has studied a bit of Physics and has a degree in Computational Linguistics, as well as a PhD in Bioinformatics. He has worked in Zurich, London and Melbourne in a number of different companies and industries. Ranging from a media management system for police agencies to ad tech. He is currently the tech lead for the recommendations team at SEEK’s AI Platform Services department.

Protecting data…but from who?

A profile of the current state of data breaches, bad actors & attack types with guidance along the way on what you can do to address this in your organization.

David Grice

David Grice - Security Architect @ ANZ Bank

David works as an embedded security architect inside a data science and analytics team at ANZ. He guides and helps implement their overall security program by working closely with developers, ops & SRE on application and data security. David has a strong cyber security background in a range of roles amongst financial services and other highly regulated industries and has previously presented at a number of security conferences around Australia.

More topics & speaker bios will be announced as we get closer to the date of the EDSA Conference...

Sponsors

Deep Dive with Dataiku

Small Group Sessions

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI. Dataiku believes that those companies who succeed in deploying and scaling AI will do so by ingraining a culture of working with data throughout the enterprise instead of siloing it into a specific team or role. To make this a reality, Dataiku provides one simple UI for data wrangling, mining, visualization, machine learning, and deployment based on a collaborative and team-based user interface accessible to anyone on a data team, from data scientist to beginner analyst. At the Enterprise Data Science Architecture Conference, you will be able to participate in a small-group sessions on the practical deployment of machine learning solutions with Dataiku.

Are we the right audience for you? Become a sponsor. Email winning@edsaconf.io

Sponsors - Correct Audience

Reach the right audience. Our attendees work with architecture, data infrastructure, data security, artificial intelligence, data science, software engineering and everything in between. If this is the audience that you want to reach, then email us at winning@edsaconf.io


Our Venue is the Melbourne Marriott Hotel

Conference Venue

Our venue is the Melbourne Marriott Hotel. This luxury hotel provides unparalleled elegance and world-class service. It is conveniently located in the Melbourne CBD at the Corner of Exhibition and Lonsdale Streets. Conference delegates will enjoy morning tea, lunch, afternoon tea and evening canapes. We will be there on 27th March 2020.


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See you at the Enterprise Data Science Architecture Conference!

When


Friday 27th March 2020

Where


Melbourne Marriott Hotel
Corner of Exhibition St. and Lonsdale St.
Melbourne VIC 3000
Australia