Dr. Michael Barrowman, PhD

Dr. Michael Barrowman, PhD

Data Scientist

Evolution Software


Dr. Michael Barrowman is a Data Scientist, currently employed by Evolution Sofware, a company which manages online casinos and builds their internal software structure. With a background in both the public and private sector and a wealth of experience working with medical, education and financial datasets; he has produced stunning visualisations for previous teams as well as publication-ready reports and production-ready scripts.

He has recently completed his doctoral Thesis on Multi-State Clinical Prediction Models in Renal Replacement Therapy, earning him a PhD from the University of Manchester. His PhD project encompasses the development and validation of a multi-state clinical predication model, as well as the methodological advancements to produce such a model. This has led to multiple publications and the creation of software as a by-product.

He is interested in Data Science, particularly using R and python to their fullest potential, encouraging others to do the same and is an advocate for neat and reproducible coding practices. He enjoys web development and learning about web paradigms as wel as learning new programming languages such as C++ and Typescript.

He lives in Merseyside, UK with his partner, two children and two step-children. He enjoys walks down by the local canal, through nearby forested areas and trips to the park as often as possible as his daughter’s favourite outdoor activity is “going on adventures”.


  • Data Science
  • Financial Risk Modelling
  • Clinical Prediction Modelling
  • Multi-State Models


  • PhD in Medicine, 2022

    University of Manchester

  • MSci in Mathematics, 2013

    University of Lancaster








Data Visualisation



Power BI




Data Analyst & Scientist


Nov 2022 – Present Manchester, Greater Manchester, UK
Analysing customer and transactional data to build dashboards, interact with stake holder APIs and develop business driven models to improve performance of our softwares and ease the customer journey

PhD Candidate

University of Manchester

Oct 2016 – Apr 2022 Manchester, UK
The goal of this PhD was to improve the academic knowledge surrounding Multi-State Clinical Prediction Models (MSCPMs). To accomplish this, I wrote articles to solve methodological issues that were yet to be addressed and applied these novel techniques (along with the literature) to develop and validate an MSCPM to predict outcomes for Chronic Kidney Disease patients.
(2020). Toward a Framework for the Design, Implementation, and Reporting of Methodology Scoping Reviews. J CLIN EPIDEMIOL.


(2018). Study Investigating the Generalisability of a COPD Trial Based in Primary Care (Salford Lung Study) and the Presence of a Hawthorne Effect. BMJ Open Respir Res.