The MRII Data Analysis Award, sponsored by Infotools Harmoni, recognizes individuals with exceptional skill in using data to deliver actionable insights for real-world business challenges. This year, the competition focused on issues facing the New Zealand tourism economy, prompting participants to analyze market data and provide actionable recommendations for improvement.
We are thrilled to recognize our first-place winner, Sarim Khan of Pakistan, AI Automation Engineer at Appetiser Apps, who impressed the judges with his data-driven and innovative recommendations, earning him the US $2,500 cash prize. In this post, Sarim shares his background, unique approach to the project, and his vision for how he plans to apply his data analysis skills in the future.
When I first entered the field of market research, I saw how it combined technical work with understanding human behavior and solving real business problems. That intersection has driven my career ever since.
I hold a Master’s in Computational Engineering and Mathematics, which has enabled me to work across Data Science, Machine Learning, AI Automation, and Full Stack Software Development. What this means is that I handle the complete product lifecycle, from research and planning to development and deployment. I have been fortunate enough to have worked with international startups and teams across the USA, West Asia and Europe. I’ve also worked with esteemed educational institutions like the University of Michigan Ann Arbor, all of which gave me experience of working with advanced cloud platforms and traditional on-premises infrastructure.
My expertise covers the full stack. I build and manage backend systems like data pipelines, ML models and automations, and also handle frontend development and cloud deployment. I work primarily with startups and fast-moving teams, whether they’re independent companies or units within larger organizations. My clients include AI and data startups, software engineering firms, and market research organizations. My focus is on building secure and reliable solutions to make sure they succeed after going live.
This approach came into play when working with the New Zealand tourism dataset on the Harmoni platform. I started with exploratory data analysis to understand the data and selected the question I could best answer: How can New Zealand increase visitor expenditure in the short-medium term while positioning for future growth? As for the platform itself, Harmoni is well-designed for market research. The ability to instantly turn crosstabs into charts is useful, and the statistical testing is built right in. However, there are limitations for advanced analytics work. As a web-based platform, load times are slower than desktop alternatives, and I couldn’t access raw data for custom modeling. For my analytical approach, this required some adaptation, but I used Harmoni’s strengths effectively.
Looking ahead to the next 5-10 years, I’m focused on AI automation, building more efficient ML models, and better software to solve real problems. I believe that the future is human and machine working together, not one replacing the other. My goal is to make complex capabilities accessible to more people and organizations through well-designed human-centric software development.
None of this was possible without the support and mentorship I’ve received. Thank you to my parents and sister for supporting my career path. To my wife, Hiba Shoaib, whose support makes ambitious projects possible. To Dr. Francesc Serratosa, my master’s thesis supervisor, whose rigorous approach to AI and Deep Learning research continues to influence how I tackle complex problems. And to every colleague, client, and collaborator who has challenged me and pushed me to think more strategically, this achievement reflects all of our work together.
To learn more about the MRII award programs, visit our Awards page.
