Senior Consultant

Michael Kumove

Dr Michael Kumove is a data scientist and quantitative researcher with extensive expertise in advanced analytics, machine learning, and health policy. His unique combination of academic research excellence and practical policy experience allows him to bridge the gap between complex data analysis and real-world policy implementation. With a PhD in Political Science and significant experience across international institutions, Michael brings sophisticated analytical approaches to solving complex healthcare challenges. His work spans from pioneering sentiment analysis in refugee studies to developing national health policies, demonstrating his ability to translate advanced statistical insights into practical policy solutions.

Michael’s superpower

Michael's superpower lies in his ability to apply cutting-edge data science techniques to complex healthcare policy challenges. He excels at combining advanced machine learning, causal inference, and econometric methods to extract meaningful insights from complex datasets. His background in both academic research and government policy gives him a unique perspective on how to translate sophisticated analytical findings into practical, implementable solutions. Michael's expertise in multiple programming languages and statistical frameworks, coupled with his experience in policy development, makes him particularly valuable for projects requiring both technical depth and policy awareness.

How he got here

  • Joined HealthConsult as a Senior Consultant, bringing expertise in advanced analytics, machine learning, and health policy implementation from both academic and government sectors
  • Developed groundbreaking research at ANU using fine-tuned roBERTa sentiment analysis models to create the world's first machine-coded dataset of social media sentiment towards refugees
  • Conducted innovative research at the Norwegian University of Science and Technology on demographic trends in sub-Saharan Africa, utilizing advanced machine learning and statistical modeling techniques
  • Led pioneering research at ANU on language similarity's impact on intergroup trust and post-conflict reconciliation, combining field research with advanced statistical analysis
  • Created the first national-level estimate for the fiscal cost of foetal alcohol spectrum disorders at the NZ Ministry of Health, demonstrating ability to quantify complex health impacts
  • Contributed to significant policy initiatives at the NZ Ministry of Health, including the 2015-2020 National Drug Policy and analysis of sugar-sweetened beverage taxation
  • Earned his PhD in Political Science from the Australian National University, complementing his background in Economics and Political Science
  • Strengthened his expertise through specialized training in Social Media Network Analysis and Advanced Machine Learning for Social Scientists
  • Developed proficiency in multiple programming languages and statistical tools including R, Python, Stata, and SPSS, enabling sophisticated data analysis across various platforms