Episode 216: Building Data Products from “In The Trenches” - With Ann Sebastian

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

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#657: Augmenting front-line employees with AI for better experiences, with Fabrice Martin, Medallia 22:42

cách đây 7 ngày trước22:42

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22:42

We are here recording live at Medallia Experience at the Wynn in Las Vegas, and have been seeing and hearing some amazing things about how AI can enhance the customer experience as well as enable teams at organizations to create more meaningful connections with customers. Today we’re going to talk about how AI can help to create better experiences for customers before, during, and after their interactions. To help me discuss this topic, I’d like to welcome Fabrice Martin, Chief Product Officer at Medallia. RESOURCES Medallia: https://www.medallia.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brands Don't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom Don't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company…

cách đây 2 năm trước 36:00

MP3•Trang chủ episode

Today on the Data Futurology podcast, we have Ann Sebastian, Senior Data Scientist at Wesfarmers OneDigital, as a guest on the podcast.

As Sebastian says, she is “in the trenches” building data science products. One of her key projects in recent years has been OnePass, a subscription service that provides free delivery and other services across a range of Australia’s top brands.

“It’s an incredible experience to be part of a journey, developing an idea through to proof of concept through to production ideation to a system that is adopted across the organisation,” she said. Through the podcast, Sebastian offers some key insights into that process via some of the projects that she has worked on over the years.

Sebastian also spoke about how data science teams can be built, and how a culture of innovation can be structured within them. For just one example of this that she shares on the podcast, in her current role there is a focus on learning and development, which manifests as 10 per cent of each person’s work time being dedicated to research activities.

For her part, Sebastian is currently using that research time to work on multimodal product classification, she said. “Given the fast-moving nature of retail catalogue, and need for us as a division to form a unified view across all our divisions products, there is business significance for this research project.

“We then have fortnightly quick check ins to discuss the progress on our research projects, and that really helps us to learn from each other. This is one way that data science is embedded into our day to day in a way that makes it more real for us.”

For these insights and more on how data science products are built and evaluated, and how data scientists can be motivated and innovative within their careers, tune in to the full podcast.

Enjoy the show!

Click here to learn more about OnePass

Thank you to our sponsor, Talent Insights Group!

Join us in Sydney for Ops World: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What we discussed:

0:00 Introduction

3:00 Ann talks about her experience and her remit at Wesfarmers

7:44 What are some of the use cases you’re proudest of?

15:12 Ann shares more information about her favourite use case and how it evolved from an idea to the start of the technical work.

17:58 How did you measure business impact?

20:14 How did you operationalize the models?

24:00 Can you describe your current role?

31:23 What’s your advice for people wanting to get into data science?

Quotes:

· Business teams can sometimes view data science as a mythical creature, so I love working with them to demystify data science and achieve business benefits through it.

· The use case that I'm proudest of is the automation of the complaint classification, where we implemented various natural language processing models to predict the category of the complaints using real time models.

268 tập

#Data Science #Science #Felipe Flores #Tech

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Episode 216: Building Data Products from “In The Trenches” - With Ann Sebastian

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

349 subscribers

published cách đây 2 năm trước

Chia sẻ

MP3•Trang chủ episode

Today on the Data Futurology podcast, we have Ann Sebastian, Senior Data Scientist at Wesfarmers OneDigital, as a guest on the podcast.

For these insights and more on how data science products are built and evaluated, and how data scientists can be motivated and innovative within their careers, tune in to the full podcast.

Enjoy the show!

Click here to learn more about OnePass

Thank you to our sponsor, Talent Insights Group!

Join us in Sydney for Ops World: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

What we discussed:

0:00 Introduction

3:00 Ann talks about her experience and her remit at Wesfarmers

7:44 What are some of the use cases you’re proudest of?

15:12 Ann shares more information about her favourite use case and how it evolved from an idea to the start of the technical work.

17:58 How did you measure business impact?

20:14 How did you operationalize the models?

24:00 Can you describe your current role?

31:23 What’s your advice for people wanting to get into data science?

Quotes:

· Business teams can sometimes view data science as a mythical creature, so I love working with them to demystify data science and achieve business benefits through it.

268 tập

#Data Science #Science #Felipe Flores #Tech

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cách đây 2 years trước52:34

52:34

This week on the Data Futurology podcast, we have an in-depth conversation with Conor O’Neill, the Head of Data Science at Compare The Market exploring his career journey and current role leveraging data and innovating with machine learning. When O’Neill landed at Compare The Market, he quickly found himself in a senior data role within an organisation that needed to both transform and mature its approach to data. On the podcast, O’Neill walks through the various stages of transformation, and getting the rest of the organisation aligned with that vision. He also shares some use cases that Compare The Market is effectively leveraging data for, as well as how they have been building ML products. He explains how he involves data scientists in this process and offers advice on building ML as a product when it comes to planning, delivery and infrastructure. Finally, O’Neill shares some thoughts on the difference between a data scientist’s role and that of a senior manager, and how this shifts the perspective and how a data professional will look at projects. He then rounds out the conversation with some thoughts about where data science is heading as a profession. For anyone interested in data science, O’Neill’s unconventional journey into and through the profession is both interesting and inspiring. Enjoy the show! Connect with Conor: https://www.linkedin.com/in/conoroneill1/ Thank you to our sponsor, Talent Insights Group ! Join us for our next events Advancing AI and Data Engineering Sydney (5-7 September): https://www.datafuturology.com/events Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng What we discussed 2:26: Felipe introduces Conor O’Neill. 3:23: O’Neill shares his journey from astrophysics to data science. 6:49: In astrophysics, the data sets that scientists work on are massive. O’Neill shares some insights about how he managed data in that role. 8:40: O’Neill shares his journey at Compare The Market so far. 12:04: O’Neill shares some information about a current data project that he and his team are working on. 18:08: Compare The Market had to do significant foundational work in transformation. O’Neill shares insights into that process. 21:18: O’Neill shares his experience in getting the Compare The Market organisation aligned behind their data vision. 25:12: O’Neill explains the value of having data scientists involved at the earliest stages of transformation design. 28:44: O’Neill describes his experience in moving from a data scientist role to heading a team, and the differences between these roles. 32:56: O’Neill explains some of the thinking that goes into reusing data projects, as well as how they decide the projects to not follow through. 34:04: Getting a model in front of the end users and driving adoption is a critical step – O’Neill explains how he has approached it for Compare The Market. 37:54: O’Neill overviews the various consumers of the work done by the data team, and how the data team needs to think about each of them. 40:51: Tips and guidance for creating ML as a product to be consumed internally 45:48: O’Neill shares some thoughts on how the data science industry is evolving. Key Quotes “We’ve been on a transformational journey now for a little over a year, and that’s been really good. We’ve been migrating off our legacy on-prem stack to Databricks. We’ve also been focused on getting the right people, and then also establishing a process, because if you just change the tool, you haven't fixed the issues, typically.” “You don't want your control group to be too large and you then miss opportunities. But you also don't want it to be so small that you don't get sufficient data. That's where the algorithm behind our recommendation system controls that, to optimise according to our confidence that we are or are not exceeding the required threshold, and adjust the weighting of the control group accordingly.”…

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

1
#235: Maximising the productivity of the data-led enterprise with UNSW, EG Australia and Compare the Market 39:52

cách đây 2 years trước39:52

39:52

This week we bring you a special episode of the Data Futurology podcast, featuring the keynote panel from our OpsWorld conference earlier this year featuring guests at different levels of data maturity. They shared their stories of the journey to enabling and unlocking the true value of data self-service.. The panel featured Kate Carruthers, Chief Data & Insights Officer, UNSW Sydney. She shared the university's experience, which has had a mature data environment for several years. At the other end of the table was Conor O'Neill, Head of Data Science, Compare The Market. He represented an organisation that is rapidly addressing a lack of data maturity across the organisation. The third person on the panel was Arvee Manaog, Head of Enterprise Systems, Data & Information Management, and Integration, EG Australia. She shared insights on how to effectively get organisation-wide buy-in, and then effectively educate all stakeholders on how to effectively use self-service. The panel was wide-ranging, starting off with a discussion around best practices in data self-service, before moving on to an in-depth summary of how to effectively approach self-service from each level of data maturity. There was also a robust Q & A session at the end of the panel. Through the robust audience questions, the panellists discussed strategies for ensuring data trustworthiness in self-service. They also discussed how ROI is best measured with self-service data practices. Businesses of all sizes that want to maximise data value should look at effective self-service approaches. This panel provides invaluable insights into both getting started and continuing to innovate once the data environment has been fully modernised and transformed. Enjoy the show! Thank you to our sponsor, Talent Insights Group ! Join us for our next events Advancing AI and Data Engineering Sydney (5-7 September): https://www.datafuturology.com/events Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng What we discussed: 2:07: Felipe introduces the three panelists. 3:19: Carruthers explains UNSW’s perspective around best practices in data self-service. 6:23: Manaog explains the challenges of secure self-service in EG Australia. 10:38: Manaog explains the initial steps EG Australia took to get started on the data self-service journey. 14:40: O’Neill describes some self-service approaches he's seen work well. 19:50: Carruthers describes how UNSW has kept engagement with DevOps-created dashboards and models high across the organisation. 22:50: The panel takes audience questions, with the first being “How do we influence and motivate data silo owners to share for indirect enterprise outcomes?” 27:07: How can a mature data organisation bring together data literacy and digital literacy across users? 28:11: For a less mature data organisation, how can data leads ensure data trustworthiness in self-service? 30:14: There are trade-offs involved in self-service models. How can those be managed in the pursuit of a self-service culture? 35:38: What are the most effective techniques for measuring ROI with self-service data practices? Key quotes: Manaog: “We’re using DataIQ. And it actually helps because it's easier for users. I got a good adoption rate for that because it’s possible to do drag and drop, there are recipes and users don't need to code. They can easily do their analysis, create their workflows and then come to the hub and say, can you productionise this?” O’Neill: “In one model, we're doing a hub and spoke approach, where we have champions placed within the business units. We are working with those champions to ensure that we understand how they're using the report. It’s not just what they want to see. But in practice, what are they doing with it?”…

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Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science « » Episode 216: Building Data Products from “In The Trenches” - With Ann Sebastian

Episode 216: Building Data Products from “In The Trenches” - With Ann Sebastian

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Episode 216: Building Data Products from “In The Trenches” - With Ann Sebastian