Value Driven Data Science

The launch of Chat-GPT turned the business world upside down and left many people wondering about the future of their careers. How do you compete against AI? One solution is by delivering a superior customer experience.

In this episode, Dasun Premadasa joins Dr Genevieve Hayes to discuss why technical people often trip up when it comes to customer experience and what data scientists can do to overcome these issues.

Guest Bio

Dasun Premadasa is the founder of DASCX, an independent business analyst consultancy that helps businesses with their digital transformations and IT project delivery. He is also the host of the DASCX Show on YouTube.

Talking Points

• How delivering a superior customer experience can boost your value as a data scientist.
• Why technical people, such as data scientists, tend to neglect CX.
• What does good CX look like?
• The consequences of bad CX for data scientists and end users.
• The importance of identifying the right customer when pitching a data science solution.
• Strategies data scientists can employ to improve the experience of their end user.

Links

• Connect with Dasun on LinkedIn
• DASCX Show episode with Dasun and Genevieve
• DASCX
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

From social media to electricity grids and the internet itself, we live in a highly interconnected world. But traditional data science techniques don’t adequately allow for the relationships that can exist between data points in such networks. This is where graph data analysis comes into play. 

In this episode, Dr Alessandro Negro joins Dr Genevieve Hayes to discuss how data scientists can exploit the natural relationships that exist within network datasets through the use of graph-powered machine learning.

Guest Bio

Dr Alessandro Negro is the Chief Scientist at GraphAware, the world’s #1 Neo4j consultancy, and Managing Director at GraphAware Italy. He is also the author of Graph-Powered Machine Learning and the recently released Knowledge Graphs Applied.

Talking Points

• What is graph data and how does it differ from structured data?
• Use cases for graphs and graph databases?
• What is a knowledge graph, how are they created and what are their benefits?
• How can graphs be used to power machine learning?
• How can machine learning algorithms be used to build knowledge graphs?
• Steps data scientists can take to get started with graph data science and knowledge graphs.

Links

• Connect with Alessandro on LinkedIn
• Graph-Powered Machine Learning
• Knowledge Graphs Applied
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Data science is an in-demand skill. Yet, many data scientists find it challenging to get started in the industry and to differentiate themselves from other data scientists once they find a job.

In this episode, Jonathan Stark joins Dr Genevieve Hayes to discuss how data scientists can find their niche and build a reputation as a data science authority.

Guest Bio

Jonathan Stark is a former software developer who now helps independent professionals make a living while increasing their impact on the world. He is the author of Hourly Billing Is Nuts, the host of the podcast Ditching Hourly and the co-host of The Business of Authority.

Talking Points

• How data scientists can build their authority and move away from being viewed as commodities.
• The benefits of specialisation, both as an independent professional, and as an employee of a larger organisation.
• Is it necessary to manage staff in order to establish your credibility as an authority in data science?
• How your authority as a data scientist, once established, could potentially be leveraged both within the corporate world and as a springboard into an independent career.

Links

• Jonathan’s Website
• Ditching Hourly
• The Business of Authority
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

“Data science unicorns” are those rare people who “understand the (data) problem they seek to resolve, have the mathematical expertise to analyse the problem and possess the computing skills to covert this knowledge into outcomes.” In fact, they are considered so rare that some people have suggested they don’t really exist. Yet, although nobody is born a data science unicorn, organisations with the right know-how can create them.

In this episode, Dr Peter Prevos joins Dr Genevieve Hayes to discuss his work in creating data science unicorns from water industry subject matter experts around the world.

Guest Bio

Dr Peter Prevos is a civil engineer, social scientist (and amateur magician) who manages the data science function at Coliban Water in regional Australia and runs courses in data science for water professionals. He is also the author of a number of books including Principles of Strategic Data Science and the recently released Data Science for Water Utilities.

Talking Points

• Why Linux is the best operating system for data science.
• How the social sciences can make you a better data scientist.
• Creating data science unicorns in the water industry.
• The similarities and differences between data science in the water industry and in other industries.
• What data scientists can learn from the world of theatrical magic.

Links

• Connect with Peter on LinkedIn 
• Peter’s website
• Computer Magic: Software Illusions and Deceptions
• Computer Science 4 Fun
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Are you familiar with “environmental justice”? It’s all about equitable access to environmental amenities and the equitable distribution of pollution, and has its roots in the American Civil Rights movement of the 1960’s and 1970’s.

In this episode, Robin Rotman and Amber Spriggs join Dr Genevieve Hayes to discuss the environmental justice movement and how open access GIS-based tools are being used to achieve environmental justice in the USA today.

Guest Bio

Robin Rotman is an Assistant Professor of Energy and Environmental Law and Policy at the University of Missouri-Columbia. She is also a qualified lawyer, focussing on energy, environmental, and natural resource issues, and is a Counsel at Van Ness Feldman, a law firm in Washington DC.

Amber Spriggs is a civil engineering Masters student at the University of Missouri-Columbia with a research focus on hydrology, hydraulic engineering, GIS-based risk assessment, and flood insurance policy.

Talking Points

• What is environmental justice?
• Why the environmental justice movement and the American Civil Rights movement are one and the same.
• The role of data and analytics in achieving environmental justice both now and when the term was first coined.
• Examples of how spatial data analysis has been used to achieve environmental justice.
• How similar techniques could potentially be used to achieve positive outcomes for the community in other ways.
• The role of data and analytics in legal proceedings relating to environmental justice.

Links

• Connect with Robin on LinkedIn
• Connect with Amber on LinkedIn
• EJScreen
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Data scientists are constantly being told of the importance of effective communication for their career success. But this advice typically translates to being able to communicate effectively the results of their work. One aspect of communication that is often overlooked is conversational communication.

In this episode, Julia Lessing joins Dr Genevieve Hayes to discuss the skills and techniques data scientists can combine to make their workplace conversations a lot easier.

Guest Bio

Julia Lessing is the principal actuary and Director of Guardian Actuarial, which specialises in helping clients use data to solve complex people-oriented problems, and runs the Guardian Actuarial Leadership Program and the Easier Conversations course. She is also the host of the We Are Actuaries podcast and has trained and served as a Lifeline phone counsellor.

Talking Points

• The importance of effective conversations in the workplace.
• Common stumbling blocks for technical people, when it comes to effective communication.
• The potential consequences of poor workplace conversations and the benefits of good conversations.
• The key skills involved in conducting an effective conversation.
• How you go about preparing for important conversations
• Conducting effective conversations within large groups and how to make meeting communications more effective.

Links

• Connect with Julia on LinkedIn
• Easier Conversations
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

In December 2022, OpenAI released ChatGPT for public testing and within a week of its launch, the user count exceeded 1 million. For many, ChatGPT provided a first glimpse at what an AI-powered future might look like.

In this episode, Dr Genevieve Hayes is joined once again by Dr David Joyner to discuss the implications of AI-driven technology, such as ChatGPT, for education, business and the world in general, and to finish their discussion of Georgia Tech’s OMSCS program.

This is the second part of a two-part conversation, which began in Episode 9.

Guest Bio

Dr David Joyner is the Executive Director of Online Education and the Online Master of Science in Computer Science at Georgia Tech’s College of Computing. Between 2019 and 2021 he taught a total of 21,768 for-credit college students, more than any other person on the planet. He is also the author of the recently released Teaching at Scale, and co-author of The Distributed Classroom.

Talking Points

• The evolution of human computer interaction.
• The role of Masters programs vs shorter courses in helping data scientists keep up with the latest technological developments.
• Why ChatGPT is a game changer for education and business in general.
• The opportunities and challenges presented by AI chatbots, such as ChatGPT.
• The importance of understanding the context when analysing data.

Links

• David’s website
• Georgia Tech’s OMSCS
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

What if you could get a Masters degree in Machine Learning for under US$8000, from a top US university, without quitting your day job or moving location? Georgia Tech’s pioneering Online Master of Science in Computer Science (OMSCS) program offers just that. 

In this episode, Dr David Joyner joins Dr Genevieve Hayes to discuss OMSCS, the world’s first MOOC-based degree.

This is the first part of a two-part conversation, which is continued in Episode 10.

Guest Bio

Dr David Joyner is the Executive Director of Online Education and the Online Master of Science in Computer Science at Georgia Tech’s College of Computing. Between 2019 and 2021 he taught a total of 21,768 for-credit college students, more than any other person on the planet. He is also the author of the recently released Teaching at Scale, and co-author of The Distributed Classroom.

Talking Points

• What is the OMSCS?
• How OMSCS compares to other Computer Science Masters programs and MOOCs?
• How online education can help data scientists keep pace with the rapidly changing technological landscape.
• Challenges and opportunities associated with teaching and learning in the online space.
• Why Georgia Tech students talk about “getting out” instead of “graduating”.

Links

• David’s website
• Georgia Tech’s OMSCS
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Ever since Facebook rebranded itself as Meta, the term “metaverse” has entered everyone’s vocabulary, but there’s still a lot of confusion about what it actually is and how it’s likely to affect our lives in the future. 

In this episode, Romeo Cabrera Arévalo, a data scientist working in the immersive technology space, joins Dr Genevieve Hayes to answer these questions and more.

Guest Bio

Romeo Cabrera Arévalo is a senior AI and computer vision researcher and engineer at Immersed, “the world’s first professional metaverse.” He is also an AI and tech advisor to the Board of Laboratorio iA, and has lectured in the Masters of Data Science program at the Escuela Superior Politéchnica del Litoral.

Talking Points

• What is the metaverse and why should people care?
• The difference between virtual reality, augmented reality and mixed reality.
• The potential benefits of immersive technologies, both now and in the future.
• The role of AI, data science and machine learning in the metaverse.
• The types of algorithms and techniques that go into building metaverse technologies.
• The “uncanny valley” and the challenge of giving avatars legs in the metaverse.

Links

• Connect with Romeo on LinkedIn
• Immersed
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Over the past decade, demand for data talent has grown exponentially, and this has had a massive impact on talent acquision in the data space. Employers of data professionals frequently cite talent acquisition as one of the biggest challenges they face in building their internal data capabilties. 

In this episode, Dr Genevieve Hayes is joined by data recruiter Joel Robinstein to discuss the data science recruitment landscape, including practical advice for both data scientists and those looking to employ them.

Guest Bio

Joel Robinstein is Head of Clients Services and Operations at Precision Sourcing Australia, where he has over 12 years’ experience working in the data recruitment space. He is also the co-host of the podcast Keeping Up With Data.

Talking Points

• The evolution of the data science recruiting space over the last 10 years.
• What employers look for when hiring data staff, what data scientists look for in prospective employers, and how this varies by role seniority.
• Strategies organisations can employ to identify, attract and retain data talent.
• What makes a great data science leader.
• Career paths available to data scientists and how you can make them happen.

Links

• Connect with Joel on LinkedIn
• Keeping up with Data podcast
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE