From personal, through team and departmental, to organizational – the importance of brand within the data sector has arguably never been more keenly felt than it is now. And with brand comes influence.

Utilising brand to influence in areas like talent acquisition, self-promotion, side hustles and gigs and general thought leadership and community activity is now a key component part of a data leader’s toolset.

Dr. Adam Sroka is founder and director at Hypercube Consulting, a firm that helps organisations unlock value from data by delivering enterprise-scale solutions and building high-performing data and analytics teams from the ground up. With over 10 years of experience in data science, machine learning, and artificial intelligence, Adam is a recognised expert and speaker in his field.

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Content Analytics is the practice of understanding exactly what content your organisation currently possesses, how effectively this content is being utilised and what influence this utilisation can have on your consumers or customer’s behaviour!

It’s all about “reading the trails” that are left behind by people (and systems!) as content is delivered, discovered, and consumed.

Megan Reutin is Global Head of Data Science & Strategy at Grunenthal Group. She’s an expert in Artificial Intelligence, social media, and Data Science. Twice Inspirational Woman of the Year finalist, she’s a bilingual thought leader who is a passionate advocate of inspiring future generations into technology and data careers.   

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We are all acutely aware of the need for the data industry to attract a constant flow of new talent.

However, a quick glance at any available data will tell us that there’s a huge challenge in ensuring that the industry is able to educate, inspire, and attract young minds during their journeys from classroom to employment.

Rachel Keane is the founder of the Data Inspiration Group and the digdata programme – a virtual work experience offering that develops key employability skills in students across secondary and tertiary education. Prior to this she co-founded Women in Data and worked as a data & analytics recruitment consultant for 12 years.

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Measurement in Data Science is a defining element of any proposed project.

What, why and how we measure can often be some of the major factors in determining the success or otherwise of the piece of work that is subsequently carried out.

The Measurement Mindset recognizes the critical importance of measurement and places it firmly alongside other factors such as domain expertise and communication skills as essential parts of a Data Scientist’s toolkit.

Indre Stanaityte, freelance data expert and entrepreneur, thrives on unravelling 'immeasurable' challenges, turning them into creative, impactful results.

Her journey, from poker enthusiast to business founder, is marked by significant project successes with brands such as Nissan, British Gas and Jaguar Land Rover and innovative approaches and solutions. 

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Impact in Data projects is the alpha and the omega. It’s the reason why the Data function exists in the first place and the factor that causes so many people to study and work so hard to enter the industry. However, it’s not all plain sailing. When data projects go wrong, it’s often because they fail to deliver the impact that their owners and sponsors have promised. Impact is tangible, measurable, and simple to recognise – and can be the difference between success and failure for a Data leader.

Dr Andrew McMahon is Head of MLOps for Data Innovation at Natwest, author of the recently published “Machine Learning Engineering with Python”, was awarded the title “Rising Star of the Year” at the 2022 British Data Awards and was the Data Science Foundation’s “Data Scientist of the Year” for 2019

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The Data industry traditionally encourages strong links between commercial organisations and academia.

From guest lecturing to internships to research posts and incubator spinouts, the lines between what can be two very separate and distinct communities in other industries seem to be blurring more and more every year.

However, there are some recognisable differences between the two domains.

Dr. Jasmina Lazic is Head of Research & Development at Bigtincan and former Chief Data Technologist at the Bayes Centre, University of Edinburgh.

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In this episode, we take a deeper dive into The Importance of Purpose in Work

Our research has found that, over the last few years, data professionals have increasingly started to think about why they do the jobs that they do.

If they can do the job that they want, for any company they choose, almost anywhere in the world, why stay at the one they are currently at — or what could potentially tempt them to look elsewhere?

Donne Burrows is Co-Founder & Chief Operating Officer of Engine B.

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In this episode we take a deeper dive into Diversity in the workplace.

As increased globalisation and remote working patterns have presented themselves because of recent societal events, opportunities for organisations to attract and retain a more diverse and inclusive data talent pool have never been better.

However, it remains to be seen whether some of the widespread gains in DE&I that the last two years have presented are a fundamental change in the data talent landscape or a temporary blip.

Elizabeth Hollinger is Director of Insights, Data and Applications Development at Aggreko.

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Globalisation has been a theme of data talent acquisition strategy for several years now.

However, events such as Brexit, pronounced local talent shortages and the societal impact of the recent pandemic have accelerated many organisations towards more widely adopting work from home, work from anywhere and remote/hybrid work combinations.

Stephen Garland is Chief Technology and Product Officer at Trustpilot

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The data talent landscape has changed forever over the last few years with the impact of globalisation, remote working and the increasing demand for scarce human resources.

These factors, and others, have caused a seismic shift in the ways in which organisations must structure their reward packages to both attract, and retain, data professionals.

Increasingly, elements beyond a competitive salary and flexible working pattern are required to secure access to the best data talent.

Scott Leishman is Global Head of People & Talent at Vector.AI, and a veteran tech and data reward specialist.

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