I spent the first 23 years of my life in Southern Estonia. Life in Estonia was peaceful and beautiful - I love my language, country, and people deeply - but I knew that my ambition would sooner or later take me abroad. I come from a humble working class family and I’m the first in my family to ever go to college. My parents are the people I owe all my work ethic to. Fun fact - my grandmother Virve has never visited the capital of Estonia (which is a few hours drive from her). Meanwhile, I have lived in six countries. Not sure where I get my travel bug from!

My journey to public health and health data science has been far from linear. My bachelor’s was in political science - albeit, quantitative political science, because statistics always made more sense to me than qualitative methods. I was heading towards a career in diplomacy and even interned at the Ministry of Foreign Affairs in Estonia, Embassy in Dublin, and the UN Human Rights Council in Geneva. It was only during my master’s at Sciences Po Paris, that I decided to switch to healthcare. My heart was set after a life-changing internship at WHO regional office in Cairo, Egypt.

I am passionate about leveraging the ever accumulating healthcare data, including electronic health records data, to answer various healthcare questions. Over the years, I’ve gained a lot of different skills - from programming in SQL, Stata, R, and Python, to different methodologies such as biostatistics and econometrics. I believe that my greatest strength is that I’m trained in both predictive modeling (such as supervised and unsupervised machine learning), as well as causal inference modeling that allows us to understand the real effect that different actors have on one another. The latter is important as it can guide public health interventions and randomization may not always be ethical or feasible.