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Matthew Fryer, VP and chief data science officer, Expedia Group

Path to power

 

I started my career in OR/analytics at British Airways improving airport and commercial decisions over six years, rising to senior consultant. Following BA, I spent four years at Debenhams as the OR manager covering store location, space allocation, ranging optimisation and general analytics. I moved to Expedia Group/hotels.com, building and leading the analytics team of 60-plus professionals, rising to VP analytics, transforming from an EMEA focus to a global focus. The role encompassed all analytics/data aspects, including MVT testing, BI, data product management, customer analytics and more. My current role is to create, build and lead a dedicated data science and AI function owning all aspects of the algorithmic lifecycle. I lead highly-skilled teams of data scientists and the engineers/product managers of our machine learning platforms, reporting to the brand president and part of the senior leadership team. Algorithms are a fundamental part of the Expedia Group/hotels.com strategy including our main marketplace matching algorithm, optimising content and marketing using deep learning among hundreds of other use cases. I was awarded the inaugural Machine Learning Hero award by Amazon Web Services in Q4 2018.

 

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

 

Wow, this is a tough question - there have been many. If I had to pick one, it would be building out the data science/AI team and strategy influencing the whole organisation to move to an AI-first approach. Seeing the improvement in customers’ experiences that has come from using AI is immensely rewarding.

 

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

 

Fundamentally, always remain curious with a thirst for constant learning. I would add a close second of learning how to influence stakeholders, especially how to explain your work as a story. As Marshall Goldsmith said, what got you here, won’t get you there.

 

Did 2018 turn out the way you expected? If not, in what ways was it different?

 

In many ways, 2018 turned out the way I expected and often exceeded those expectations, including many of the key events of 2018 such as GDPR implementation and Brexit planning, to name a couple. The travel market is incredibly fast-paced, hence you need to be resilient and to expect the unexpected. Usually, what you plan at the start of the year is very different from the eventual work. Outside of data/analytics, I think the most unexpected was England getting to the semi-finals of the World Cup.

 

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

 

I think some of the key themes of 2018 will minimally continue and likely increase in pace in 2019 such as: machine learning/AI, data governance/privacy, self-service analytics/automated machine learning, data quality and availability, streaming-first thinking, integrated data/attribute stores, cloud platforms/services, challenges finding talent (especially diverse talent). The one area I suspect will see a much larger leap is the value placed on data and analytics/AI skills in senior leadership and boards across industries, governments, etc.

 

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

 

Overall, we apply a similar data-driven approach to this challenge as to others in the business, including applying data analytics to the funnel and experimenting with all aspects of the hiring approach. This is especially key to create diverse teams which I think is a still a very significant issue for our industry. I am very proud of our new internal machine learning and data academy. Building skills and facilitating career changes from within is critical for retention through to creating new future talent. It is a buyer’s market in a number of skill areas. We focus on being the most attractive choice for key talent from interns through to experienced professionals.

 

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

 

The positive impact from machine learning and AI. I think the combination of the significant value they deliver, immense variety of use cases, increased talent availability, quality and maturity of the algorithms and technology with the power of deep learning academic and industry research mean these are now must-haves for any organisation.

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