Building authority as a data professional doesn't require a large budget, a publisher, or even a large audience. But it does require a deliberate decision to share your thinking with the world and the patience to let that compound over time.

In this Value Boost episode, Prof. Rob Hyndman joins Dr. Genevieve Hayes to share how selectively giving away his work for free helped him become one of the most cited and influential statisticians in the world, and what data professionals at any stage of their career can learn from that approach.

In this episode, you'll discover:

1. Why Rob decided to give away his work for free from the start of his career [01:42]
2. How open source software multiplied the impact of his research [05:58]
3. Why authority building is a virtuous cycle and how to start it [09:47]
4. Why starting small is the right move [10:35]

Guest Bio

Prof. Rob Hyndman is one of the world’s most influential applied statisticians and a Professor in the Department of Econometrics and Business Statistics at Monash University. He has maintained an active statistical consulting practice for over 40 years, published over 200 research papers, co-authored more than 65 R packages and written five books on time series forecasting. He is also a Fellow of both the Australian Academy of Science and the Academy of Social Sciences in Australia.

Links

• Rob's website
• Otexts' website
• 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 today are under pressure to adopt the latest tools - machine learning, LLMs, generative AI. But in the rush to embrace what's new, many are leaving some of the most powerful analytical tools sitting on the shelf. Tools that handle something modern AI largely can't: uncertainty.

In this episode, Prof. Rob Hyndman joins Dr. Genevieve Hayes to make the case for why rigorous statistical thinking remains indispensable in the age of AI, and what data scientists are giving up when they abandon it.

In this episode, you'll discover:

1. Why throwing data at an LLM is no substitute for building a model that understands the problem [04:27]
2. How combining classical statistics and machine learning can produce better forecasting results than either approach alone [08:22]
3. What data scientists lose when they stop thinking probabilistically - and why it matters for decision making [12:38]
4. Where to start if you want to strengthen your statistical foundations [25:10]

Guest Bio

Prof. Rob Hyndman is one of the world’s most influential applied statisticians and a Professor in the Department of Econometrics and Business Statistics at Monash University. He has maintained an active statistical consulting practice for over 40 years, published over 200 research papers, co-authored more than 65 R packages and written five books on time series forecasting. He is also a Fellow of both the Australian Academy of Science and the Academy of Social Sciences in Australia.

Links

• Rob's website
• Otexts' website
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

Over 100 episodes of conversations with world-class practitioners, a few ideas keep surfacing. Technical skill is necessary but never sufficient. The most valuable data professionals aren't the ones who build the best models - they're the ones who know which problems are worth solving. And the gap between those two things is where most data scientists are leaving value on the table.

In this milestone episode, Dr. Genevieve Hayes reflects on her career journey and the conversations that helped her arrive at these conclusions, with Matt O'Mara turning the tables to put her in the hot seat.

In this episode, you'll discover:

1. From statistician to machine learning advocate and back again - and what that journey revealed [09:49]
2. The crack in the data science skills market where significant value is hiding [18:59]
3. Why knowing which problems to solve matters more than knowing how to solve them [24:53]
4. The top three lessons from 100 conversations on what data science value actually means [33:49]

Guest Bio

Matt O'Mara is the Managing Director of information and insights company Analysis Paralysis and is the founder and Director of i3, which helps organisations use an information lens to realise significant value, increase productivity and achieve business outcomes. He is also an international speaker, facilitator and strategist and is the first and only New Zealander to attain Records and Information Management Practitioners Alliance (RIMPA) Global certified Fellow status.

Links

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