Mark Atterbury

Managing Consultant


  • > Leading analytics & data exploitation programmes
  • > DataOps (continuous delivery for data)
  • > Engineering cloud-native analytics & data solutions
  • > Data services design and management
  • > Operationalisation of advanced analytics, at scale
  • > Data science value creation and ROI  


I embraced data early on, taking a statistics GCSE and degree at the University of Bath. After working for GSK and completing Teach First early on in my careerfound that both the IT and business communities had finally caught up with the fact that data was cool 

Now with more options than banking or actuarial science; moved professions to focus on analytics. A childhood spent breaking the family computer paid off working for IBM as an advanced analytics consultant, partnering frequently with their digital organisation on complex implementations; before joining DMW in 2017.  

 I’m a shameless foodie, so enjoy spare time cookinghoning my knowledge of new food trends, and consequently; running. 


I focus on bringing together the best of lean, agile, systems thinking, DevOpsCI/CD and applied data science to help clients develop sustainable capabilities and solutions in the context of data insight.  

As such, I focus on “what good looks like” in bringing together often highly technical IT services, skills-oriented analyst capabilities, and knowledge-oriented business stakeholders, to help clients deliver innovation at pace, but also ensure they deliver value. DevOps + Data isn’t always enough. 

I’m a strong advocate for a focus on people in analytics delivery, regardless of how technical it isHow you consume insight and analytics services is more important than what they provide.  

Career Highlights 

My most recent work has been as a service design and delivery lead for a major data platform capability at a FTSE100 client, helping them take DataOps to the masses, and building out a distributed compute analytics capability on AWS. 

In previous roles I’ve implemented the data science algorithms behind an app placing freezers (globally) for a consumer packaged goods client, designed a fraud and error detection solution supporting a major government benefitand led a SAFe-led data science team for an online retailer. 

This has led to a wide range of experience in the context of analytics; ranging from modelling bayesian networksto value creation using agile and design thinking, to service implementation and infrastructure availability management.

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