Value Driven Data Science

Decision-making is an essential part of everyday life and one of the main applications of data science is making the decision-making process easier.

However, mostly when data scientists build models, it’s to make a single decision. But in real life, decision-making is rarely that simple.

In this episode, Prof Warren Powell joins Dr Genevieve Hayes to discuss one way in which the decision-making process can become more complicated, in the form of sequential decision problems.

Guest Bio

Warren Powell is the co-founder and Chief Innovation Officer of Optimal Dynamics and a Professor Emeritus after retiring from Princeton, where he was a faculty member in the Department of Operations Research and Financial Engineering. He is also the author of Sequential Decision Analytics and Modelling and Reinforcement Learning and Stochastic Optimization.

Talking Points

• What is a sequential decision problem?
• Real-life examples of sequential decision problems and the disciplines in which they occur.
• The four main classes of techniques for solving sequential decision problems.
• How Warren’s approach to addressing sequential decision problems differs from the standard approach in this space.
• The challenges of implementing sequential decision analysis techniques in practice.

Links

• Connect with Warren on LinkedIn
• Warren’s website (SDA Links)
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

According to the Interview Valet 2023 State of Podcast Guesting Annual Report, there are over 380,000 active podcasts in the world right now, with the average podcast episode receiving just 150 downloads within 30 days of its release.

So, for individuals and organisations looking to use podcast marketing to grow their business, just booking podcast guest appearances isn’t enough. It’s necessary to use a targeted strategy based on data.

In this episode, Tom Schwab joins Dr Genevieve Hayes to discuss how Interview Valet uses data to optimise business results in podcast interview marketing.

Guest Bio

Tom Schwab is the founder and Chief Evangelist Officer of Interview Valet and the author of Podcast Guest Profits and One Conversation Away. He is also an engineer whose first job out of college involved running nuclear power plants in the US Navy.

Talking Points

• What is podcast interview marketing and how it differs from traditional digital marketing approaches?
• How Tom uses data to inform podcast guest marketing strategies at Interview Valet.
• The most important metrics for targeting podcast marketing and optimising return on investment.
• What makes a top podcast?
• How Tom’s use of data and analytics has evolved over time.

Links

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

Start-ups and data science go hand in hand, but usually when people think about how data science can help start-ups, it’s with regard to product development and enhancement. However, it doesn’t matter how great a start-up’s product is, if the financials are a mess, the business is going to struggle.

This is where data science can also help start-ups, in the form of financial modelling and analysis.

In this episode, Lauren Pearl joins Dr Genevieve Hayes to discuss her work in helping start-up founders translate their business ideas into maths via financial models.

Guest Bio

Lauren Pearl is a CEO-turned-CFO who helps start-up founders work better with financial data. She holds an MBA from NYU’s Stern School of Business and is the resident start-up finance expert at NYU’s Berkley Centre for Entrepreneurship.

Talking Points

• What is meant by financial modelling?
• The challenges of building financial models with little or no data.
• Why is it important for founders to understand their financials.
• The potential consequences of not understanding financial data.
• How founders can use data and technology more generally to help in running their business.

Links

• Connect with Lauren on LinkedIn
• Lauren Pearl Consulting
• 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 among the most in-demand skills of the 21st century, with opportunities existing for data scientists to make a difference and earn good money as an employee in a range of industries. Yet there has also never been a better time to be a data science entrepreneur (or datapreneur).

But for data scientists who have never experienced the entrepreneurial life and who are used to the security of a steady pay check, making the transition from employee to entrepreneur may seem like an impossible leap, regardless of how desirable it may seem.

In this episode, David Shriner-Cahn joins Dr Genevieve Hayes to discuss how data scientists can escape the corporate world and make the transition from employee to datapreneur.

Guest Bio

David Shriner-Cahn is the podcast host and community builder behind Smashing the Plateau, an online platform offering resources, accountability, and camaraderie to high-performing professionals who are making the leap from the corporate career track to entrepreneurial business ownership.

Talking Points

• How entrepreneurship differs from being a regular employee, particularly with regard to mindset.
• The advantages and disadvantages of each way of making a living.
• Making the transition from employment to entrepreneurship and how to gauge if entrepreneurship is right for you.
• Building your network as an entrepreneur.
• How taking a sabbatical can help ease the transition between being an employee and an entrepreneur.
• The value of community.

Links

• Smashing the Plateau
• Connect with Genevieve on LinkedIn
• Value Driven Data Science has recently featured in Feedspot’s list of the 4 Best Australian Data Science Podcasts. Be among the first to hear about the release of each new podcast episode by signing up HERE

Depending on who you speak to blockchain and cryptocurrency are either the way of the future or the scam of the century. But few would be able to tell you what either of them actually is – including among data scientists for whom data and technology are a way of life. 

In this episode, Luke Willis joins Dr Genevieve Hayes to demystify blockchains, cryptocurrency and the data behind them.

Guest Bio

Luke Willis is the dApp UX guy. He’s a web3 developer with extensive front end and UX experience. He’s also the founder of the Koin Press where he writes a regular newsletter, hosts the Koin Press podcast and helps others make their dApp ideas a reality.

Talking Points

• What is the blockchain?
• The different types of blockchains and the differences between them?
• How the blockchain relates to cryptocurrency.
• What is a dApp and Luke’s experiences in building them.
• How data is stored on the blockchain and how it can be accessed.

Links

• Luke’s Website
• Koinos Blocks
• Koiner
• Etherscan
• Connect with Genevieve on LinkedIn
• Be among the first to hear about the release of each new podcast episode by signing up HERE

When data science first became the must-have skill of the 21st century, organisations were fighting to recruit the best and brightest data science talent. But the glory of having a data scientist on staff was often short-lived, as many organisations soon found they didn’t know what to do with them.

Business leaders had been sold the dream of being able to turn their data into business gold but were unable to maximise the value of the data science expertise they had brought in because they couldn’t communicate effectively with their new data science teams.

In this episode, Dr Howard Friedman joins Dr Genevieve Hayes to discuss how adopting a customer mindset can help business leaders capitalise on the hidden value of data.

Guest Bio

Dr Howard Steven Friedman is a data scientist, health economist, and writer with decades of experience leading data modelling teams in the private sector, public sector and academia. He is an adjunct professor, teaching data science, statistics, and program evaluation, at Columbia University, and has authored/co-authored over 100 scientific articles and book chapters in areas of applied statistics, health economics and politics. His previous books include Ultimate Price and Measure of a Nation, which Jared Diamond called the best book of 2012.

Talking Points

• How Howard’s personal experiences informed the writing of Winning with Data Science.
• What business leaders should know, in order to be effective customers of data science teams.
• How important is it for business leaders to be up to date with the latest data science trends and buzzwords?
• What data scientists should know in order to work more effectively with business leaders.
• Howard’s previous book, Ultimate Price.
• How data scientists and economists go about placing a price on human life.

Links

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

Correlation does not equal causation, as anyone who has studied statistics or data science would know. But understanding causality isn’t just important when you’re developing models.

If you’re working in business and want to be recognised for your work, it’s essential to be able to demonstrate causality between what you do and the benefit flowing through to the business.

In this episode, Mark Stouse joins Dr Genevieve Hayes to discuss how data science can be used to comprehend the underlying cause-and-effect relationships in business data.

Guest Bio

Mark Stouse is the CEO of Proof Analytics, an AI-driven marketing analytics platform. Prior to becoming an analytics software CEO, Mark had a successful career in B2B marketing and in 2014 was named Innovator of the Year at the Holmes Report In2 SABRE Awards for his work in tying marketing and communication investment to key business performance metrics.

Talking Points

• The benefits to organisations of understanding causality.
• How such techniques can be applied to use cases and disciplines beyond marketing analytics.
• How data scientists can drive conversations about analytics at the C-suite level to maximise their impact.
• The potential future impact of generative AI on data science and the world in general.

Links

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

The insurance sector owes its existence to data and insurers were some of the first companies to utilise data expertise. Yet, being an early adopter isn’t always as great as it seems. And many big insurers are now discovering the challenges of bringing their long-established data systems into the 21st century.

In this episode, Maria Ferrés joins Dr Genevieve Hayes to discuss the complexities of creating order from data chaos in the insurance industry.

Guest Bio

Maria Ferrés is an actuary with extensive experience throughout Europe and Australia, who now specialises in establishing the enterprise data functions of multinational insurers. She is currently the Enterprise Data Officer at trade credit insurer Atradius and she also advises companies within the insurtech space on the use of data to comply with Data Protection laws.

Talking Points

• The ideal state of an insurer’s enterprise data capabilities.
• How to transform insurers’ data capabilities from their present, often chaotic state, to this ideal.
• The challenges in transforming insurers’ data capabilities.
• Where data scientists fit into the transformation process.
• How to overcome resistance encountered while transforming the data capabilities of an organisation.
• The impact of the GDPR on enterprise data capabilities and on the work of people using insurance data, including data scientists and Insurtechs.

Links

• Connect with Maria 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

ChatGPT was one of the best things to ever happen to data science – not so much because of what it can do, but because, virtually overnight, it made AI and data science mainstream. 

However, while most data scientists now have experience with ChatGPT and other large language model (LLM)-based technologies as end users, few have had experience in building their own LLM-based tools.

In this episode, Dr Mudasser Iqbal joins Dr Genevieve Hayes to discuss the data science behind LLMs and how to go about doing just that. 

Guest Bio

Dr Mudasser Iqbal is the Founder and CEO of TeamSolve, a company dedicated to leveraging AI for digital transformation with a sustainable focus. He has extensive experience in Industrial AI, including multiple patents, and was recognised as an MIT Young Innovator. He also played a key role in the growth of his previous start-up, Visenti, and its subsequent acquisition by Xylem Inc.

Talking Points

• The data science behind LLMs.
• How TeamSolve’s Lily, compares to ChatGPT and the advantages of a domain-specific, private chatbot, such as Lily, over a more general, public chatbot, such as ChatGPT.
• How knowledge graphs can be combined with LLMs to overcome many of the shortcomings of LLMs.
• The changing attitudes of organisations around the use of generative AI tools.
• What the emergence of cutting-edge AI tools, such as LLMs, mean for more traditional data science tools, such as analytics dashboards.
• The future of generative AI, and the potential benefits and risks to society.

Links

• TeamSolve
• Connect with Mudasser 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

Despite its conservative reputation, the financial services industry has always been a big adopter of cutting-edge technologies. Dating back more than a century, it’s also been one of the biggest employers of people with technology and data-related skills. But what does the future hold for the use of tech in the financial services industry?

In this episode, Ben Shapira joins Dr Genevieve Hayes to discuss what this future might look like and how technology is being used right now to improve the lives of consumers.

Guest Bio

Ben Shapira is a digital strategist and UX specialist turned tech entrepreneur. He is the founder and Chief Product Officer of Australian fintech start-up Dinero, as well as being a lecturer in the Master of Media and Communication program at Swinburne University.

Talking Points

• Where the financial services industry is heading, regarding the use of technology and how this will affect the lives of consumers.
• The types of data modelling and analysis that are possible because of the data produced by these new technologies.
• What is Dineiro and how data informed its creation.
• The impact of data security considerations on financial services organisations’ ability to adopt new technologies and make use of the data they produce.
• Advice for data scientists looking to build a career in marketing and advertising.
• How marketing techniques can be applied to data science to make data scientists more effective, regardless of their industry.

Links

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