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Nikolaos Kotsis, Chief Data Scientist, Network Rail

Describe your career to date

 

Following my undergraduate studies as an engineer, the data and artificial intelligence (AI) journey began with a master’s degree and PhD in related subjects, leading me to various roles within consulting and end user organisations. From these experiences, I gained significant knowledge in business operations, communication, problem-solving, decision making, and team motivation – all key ingredients for leadership. 

 

I realised that what matters most to customers is not only technical excellence, but also factors like time-to-market, return on investment, and the ability to adapt when things do not work out as expected. A common factor across my roles has been the essential integration of fact-based intelligence in decision making. 

 

In my senior positions within multinational organisations, this approach significantly contributed to growth, operational performance enhancement, improved customer experiences, and cost savings benefits. In my current role at Network Rail, I am leading the data strategy and AI capability. Our team has successfully developed products like AI-assisted solution for vegetation encroachment, property inspection, and others that are set to deliver significant safety benefits for our passengers and workforce. 

 

My responsibilities include developing a strategic vision for AI and overseeing the creation of new data management capabilities for high-quality data integration for key operations through strong collaboration with our stakeholders, ultimately aiming to improve train performance and safety. The difference between this role and my previous roles is the significant impact on society which motivates me and those who work alongside me. 

 

Additionally, I am a Visiting Professor at the University of Strathclyde where I contribute research and development in AI algorithms for predictive maintenance within railway systems, as well as other applications in medicine and biology – particularly focusing on detecting early signs of dementia which is something I am proud to be involved with. 

Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organisation? 

 

The increasing volumes of data, rapid technological advancements, and growing emphasis on speed has intensified the need for enhancing our comprehension of data and AI technologies. There is also an opportunity to leverage our business acumen, leadership skills, and data expertise to drive lasting change by solving real business problems and embedding data-driven decision making across all lines of business. 

 
To address these challenges in Network Rail, we have developed a comprehensive Data Strategy that serves as an effective approach for communicating, educating, and aligning the views and competencies required to maximise the value from data across different functions within our organisation. In addition to implementing the Data Strategy, we are developing training programmes that promote learning through practical applications in collaborative environments. This approach is particularly effective in complex concepts involving AI workflows as it allows users and senior management to experience the benefits of these technologies first-hand by participating in their development and usage. Through active participation, they become more likely to understand and endorse, this advanced technology. 

What stage has your organisation reached on its data maturity journey?       

 

As an extensive infrastructure provider with complex data ecosystems, Network Rail is currently progressing through its data maturity journey. We have made significant strides in defining our Data Strategy, working on the foundations such as data governance, investing in Cloud technology and cultivating a culture that values data-driven decision making across all levels of the organisation. 

 

However, there remains considerable work to be done throughout every part of the data lifecycle before we can fully realise the potential benefits from our valuable data assets. We need to continue developing employee data literacy, enhance our data governance framework, optimise our data architecture and infrastructure for better scalability, and ensure that we are leveraging advanced analytics based on safe AI and machine learning technologies to uncover insights in our vast amounts of data. 

 

Given the rapid progression of technology over recent years, I believe most organisations find themselves at this stage, as trying to keep up with cutting-edge innovations in data and AI requires consistent effort and considerable financial investment. By addressing these challenges and continually adapting to new technological advancements, we are confident that Network Rail can achieve an even higher level of maturity over the coming years, ultimately leading to more efficient operations, better train performance, and a reduction in passenger delays – all of which contribute positively to customer satisfaction. 

Nikolaos Kotsis
has been included in:
  • 100 Brands 2024 (EMEA)

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