Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Data scientists use optimisation every day when training machine learning models, without even thinking about it. But there's another type of optimisation - that many data scientists are unaware of - that can be used to dramatically boost the business value of your ML outputs. This second layer transforms predictions into optimal decisions, and it's where the real impact often happens.
In this episode, Dr. Tim Varelmann joins Dr. Genevieve Hayes to explain how combining machine learning with decision optimisation creates solutions that go far beyond prediction, helping stakeholders make better decisions in uncertain environments.
You'll discover:
How decision optimisation differs from ML parameter tuning [02:19]
Why combining predictions with optimisation multiplies value [13:36]
The mindset shift needed to think in optimisation terms [22:59]
How to spot immediate optimisation opportunities in your work [23:42]
Guest Bio
Dr Tim Varelmann is the founder of Bluebird Optimization and holds a PhD in Mathematical Optimisation. He is also the creator of Effortless Modeling in Python with GAMSPy, the world’s first GAMSPy course.
Links
Get Tim's 3 Step Guide to Add Optimisation to Your Data Science Skills
Bluebird Optimization Website
Connect with Genevieve on LinkedIn
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Building a model for an academic paper is one thing. Building a model that has to work perfectly during the Cricket World Cup with millions watching is something else entirely. There's no room for the kind of errors that might be acceptable in research settings or even standard business applications.
In this Value Boost episode, Prof. Steve Stern joins Dr. Genevieve Hayes to share practical lessons from deploying the Duckworth-Lewis-Stern method in high-pressure, real-time environments where mistakes have global consequences.
You'll learn:
Why model simplicity matters more than you think [02:04]
The two types of errors you need to understand [03:21]
How to test models for extreme situations [05:50]
The balance between confidence and humility [07:37]

Guest Bio
Prof. Steve Stern is a Professor of Data Science at Bond University, and is the official custodian of the Duckworth-Lewis-Stern (DLS) cricket scoring system.
Links
Contact Steve at Bond University
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE

For most data scientists, the idea of impacting the world through your work seems impossible. You may be developing technically brilliant solutions within your organisation, but seeing them become industry standards or influence global decisions feels completely out of reach.
In this episode, Prof. Steve Stern joins Dr Genevieve Hayes to share how he transformed a mathematical critique of a cricket scoring system into becoming the custodian of the globally adopted Duckworth-Lewis-Stern method - all from an office in Canberra, Australia.
This episode reveals:
How a single email response changed everything [05:24]
Why principles build trust where mathematics can't [13:19]
The "error whack-a-mole" problem that destroys credibility [16:00]
The real secret to creating work with impact [30:29]
Guest Bio
Prof. Steve Stern is a Professor of Data Science at Bond University, and is the official custodian of the Duckworth-Lewis-Stern (DLS) cricket scoring system.
Links
Contact Steve at Bond University
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE

While the transition from academia to industry can be brutal for data scientists, academics don't show up in industry empty-handed. They bring powerful transferable skills that many industry-trained data scientists never develop.
In this Value Boost episode, Dr. Sayli Javadekar joins Dr. Genevieve Hayes to flip the script on their previous conversation, exploring the valuable skills that academic-trained data scientists bring to industry and how any data scientist can develop these same strengths.
You'll learn:
The most valuable skills academics bring to industry [01:30]
Why the experimental mindset matters so much [03:43]
The hidden benefit of extended research projects [04:54]
How mentorship can work both ways for mutual benefit [07:06]
Guest Bio
Dr Sayli Javadekar is a data scientist at Thoughtworks, with experience at the World Bank and UNAIDS. Before this, she was an Assistant Professor at the University of Bath and holds a PhD in Econometrics from the University of Geneva.
Links
Connect with Sayli 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

While the transition from academia to industry can be brutal for data scientists, academics don't show up in industry empty-handed. They bring powerful transferable skills that many industry-trained data scientists never develop.
In this Value Boost episode, Dr. Sayli Javadekar joins Dr. Genevieve Hayes to flip the script on their previous conversation, exploring the valuable skills that academic-trained data scientists bring to industry and how any data scientist can develop these same strengths.
You'll learn:
The most valuable skills academics bring to industry [01:30]
Why the experimental mindset matters so much [03:43]
The hidden benefit of extended research projects [04:54]
How mentorship can work both ways for mutual benefit [07:06]
Guest Bio
Dr Sayli Javadekar is a data scientist at Thoughtworks, with experience at the World Bank and UNAIDS. Before this, she was an Assistant Professor at the University of Bath and holds a PhD in Econometrics from the University of Geneva.
Links
Connect with Sayli 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