MBN Solutions’ New Data Science Podcast, AI Right?, Breaks Down Data Science Barriers

MBN Solutions’ new monthly data science podcast, AI Right?, explores news and industry issues with a view to making the data science industry more accessible.

Launching in May 2021, the podcast brings together industry experts from recruitment, conversational AI and machine learning to help promote the accessibility of the industry and provide unique insight to industry veterans.

MBN Associate Director and AI Right? co-host, Kris McFadyen, says that AI Right is unique in its blend of industry expertise and recruitment perspectives.

“My co-hosts Andy McMahon and Megan Stamper are accomplished data scientists both with PhDs and successful careers in energy, finance and media. The three of us are able to bring together data science and recruitment expertise to help inform the industry and help show how accessible and open the data science field is as a career.”

Each month, AI Right? will review news and trends and provide expert commentary on what these trends mean for the industry from high-level data scientists to people making a career change or just starting out.

Co-host and data scientist Megan Stamper, says she’s excited to bring the podcast to the Scottish data science community.

“AI Right? is an opportunity for the data science community to come together and think about the future of data science and what it means for Scotland, especially how Scotland can become an international hub for data science, in the same way it has for FinTech and video games.”

“With AI Right? we’re hoping to give people the opportunity to engage the data science community in ways that perhaps haven’t been available to them before,” says data scientist and machine learning engineer and co-host Andy McMahon.

“Data science careers are in every sector – from television and media to banking and finance and healthcare. We want to show people that data scientists can come from every background and that there’s opportunity all across Scotland.”

In the first episode of AI Right? the trio discuss Scotland’s new AI strategy, whether AI is worth listening to, building trust and fairness, and demystifying artificial intelligence and machine learning.

McMahon says it’s an important role of data scientists and AI practitioners to help inform the public about AI and its benefits.

“It’s our jobs, as practitioners, to explain it. What is AI and machine learning and what does it do in your day-to-day life? A lot of people might not trust AI because they think it’s going to take their jobs in the next couple of years. One of the things we want to do with AI Right?, as well as celebrate data science, is inform people.”

McFadyen agrees, saying that if more people understood and embraced how AI worked and the role it plays in their lives, it could benefit Scotland’s economy and position as a global leader in AI.

“The more inclusive we can make data science and people’s understanding of AI, the more we can open the industry up to different people and push Scotland towards a technology driven future. Data science can help innovation in every sector and that innovation is often driven by more unique and diverse thinking, which you get from a bigger talent pool.”

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Host Bios 

 

Kris McFadyen

Kris is an Associate Director at data science and technology recruitment company MBN Solutions. He has worked closely with the UK and Europe’s data markets and leaders for the past six years. He brings in-depth knowledge of the data market’s talent challenges and opportunities to AI Right? 

Megan Stamper

Megan is a principal data scientist in the media industry and leads a team focusing on conversational artificial intelligence and recommendation mechanics. She has a PhD in oceanographic fluid mechanics and has previously worked for The Financial Times. 

Andy McMahon

Andy is the winner of Data Scientist of the Year at the International Data Science Awards 2019 and has worked as a lead data scientist at Streamba and Aggreko. He has a PhD in condensed matter physics and is currently focused on innovations in machine learning.