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Matthew Willis, Head of data, analytics and AI, Refinitiv

Path to power

 

After graduating in Maths and Computer Science from Sheffield University, my first job in data was building an Access database for a small hotel in Kirribilli, Sydney while on a year of travel. Stunning views of Sydney harbour and enough pocket money to keep me entertained (student-style) provided a soft landing into the world of data. In the following decade of my career, KPMG Consulting (later Atos) provided opportunities to specialise in building data warehouses and BI systems for large telcos. My next career move was to Thomson Reuters (now Refinitiv), where I have been for almost ten years now. I’ve had the opportunity to focus on my leadership skills through formal training and progressively larger roles across marketing, customer operations and technology. In my current role, I head up data, analytics and AI capabilities for Refinitiv, where I lead a global team of data technology experts who design, build and operate a suite of data and analytics platforms and services. These include AI apps that enhance business systems and processes; an analytics platform (data lake + data warehouse + data viz/BI + data science tools); financial planning and analysis systems; and application integration. This opportunity arose through the 2018 reorganisation required to separate the Refinitiv/financial and risk business from Thomson Reuters. Several technology teams across the business were brought together with the central technology business systems group, providing an opportunity to head up a team of passionate data technologists.

 

What has been the highlight of your career in the industry to date?

 

For the last two years I have worked with the Hertfordshire Independent Living Service (HILS) which provides a range of services to help older and vulnerable people stay happy, healthy and independent. The opportunity to join the HILS Board came through Thomson Reuters’ involvement with the Social Business Trust which works with corporate partners to provide expertise to UK social enterprises. Working with HILS has afforded me fantastic learning opportunities and the satisfaction of supporting a worthy cause through my data expertise. Tackling gnarly issues, driving towards exciting expansion opportunities and implementing critical governance has provided me with experiences that I can translate in my day job to better support my team and fellow leaders at Refinitiv.

 

If you could give your younger self some advice about how to progress in this industry, what would it be?

 

Get stuck into data analytics and, in particular, data visualisation as soon as you possibly can. It’s a lot of fun! Also, gain valuable experience by supporting charities and social enterprises with their data challenges at the earliest opportunity.2018 was the year when organisations realised that to power applications and realise opportunities using AI/machine learning, you need more than smart algorithms, computing power and large volumes of data. Many firms failed to deliver on the hype and excitement associated with AI due to a lack of clearly-defined problems suitable for ML techniques, process expertise, data quality and data governance.

 

What do you expect 2019 to be like for the industry?

 

A focus on techniques, process expertise, data quality and data governance for AI and ML, as well as high-value point solutions, will reap rewards in 2019.

 

Talent and skills are always a challenge to find - how are you tackling this in your organisation?

 

Partly as a result of the challenges associated with recruiting machine learning engineers, we have initiated internal training courses to up-skill high-potential employees with the data science and machine learning skills we need. Given the importance of understanding the business as well as specific technical and analytics skills, this approach has already provided a valuable flow of talent.

 

What aspect of data, analytics or their use are you most optimistic about and why?

 

With an increasing number of important data sets being made openly available online and the growth of global data science and data visualisation communities coming together to support worthy causes, I am tremendously optimistic that highly-skilled data professionals can make a difference in tackling many of the world’s challenges, from poverty and climate change to smaller local issues.Data and analytics technology/service provider

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