Tell us about your background.
I was born in a small farming town in the north-eastern part of Hungary, called Mezőkövesd. My parents moved to the capital city to work as engineers. Since they were critical of the communist regime, they were punished, and not given opportunities to earn a living wage. We lived in a small one-room house where my parents, my sister and I slept on a fold-out couch.
That all changed when the communist regime collapsed, and my parents were not hindered from getting ahead anymore. By the time I was a teenager, my father became the chief executive of the Hungarian TV channel that won the UNESCO award for best cultural television in 1999. I am proud of him, not just for that, but also for the hard years, when he taught me that principles should come before comfort. He also taught me that it’s never too late to change your career trajectory -- you should follow your passion, and figure out how to serve others with your talents.
I was much luckier than he was. I could study in the capital city in a prestigious university, learn languages, and even get a scholarship to study overseas, which brought me to New Zealand at the age of 21. I completed a Master’s degree from Corvinus University Budapest and a Master of Business degree from New Zealand's Otago University focusing on finance and quantitative studies. This gave me the unique opportunity to be able to start a career in either of these countries. At the end, love decided for me, as I met my husband while studying in New Zealand and we chose to stay here to raise our family.
How did you get interested in data science?
My mom was very dedicated to my education, and she was passionate about mathematics. She could even help me in mathematics during university, when the curriculum was quite difficult. Long before big data, digital transformation or data science had captured my interest, she sowed the seeds for a love of science into my life.
After graduation it was a struggle to find a first job that was related to my studies. Due to the panic created by the global financial crisis, reputable companies slashed or abandoned their graduate programs. So I tutored at Victoria University in Wellington, did contract jobs, and eventually got a job as a statistical and financial modeller.
I loved programming, mathematics, and statistics during university, as well as social sciences and research, but it had not come together for me in a profession. I soon learned that the bottleneck in the field of data science was not technology, but rather the shortage of professionals who could do more with data than just processing and storing it. There were still no formal or informal educational pathways.
I enrolled in every course that I could find. Stanford had a six-week course on big data that gave me an in-depth understanding of what skills I needed and what I could become. After that, I never stopped planning what to learn next: I enrolled in Coursera, DataCamp, and edEX courses, did classroom learning on cloud-computing, SAS coding, and research methods in social sciences, and I participated in research conferences. I am now back as a student at Victoria University, doing a postgraduate diploma in AI. Besides learning about new software, and familiarizing myself with new techniques, I try to learn more about the field I am most interested in: computational social science.
What are you currently working on?
MartinJenkins, the consulting firm I work for that is also sponsor of WiDS New Zealand, is building the data analytics and data science arm of their business. We have been working out where to focus in order to get to where we want to be, and are now executing a strategy for expansion. We are doing market research, investing in marketing efforts, and constantly talking to our existing and prospective clients so we can serve them better.
Part of growing a business is also taking care of the human side, and we have been working on this too -- recruiting new talent, and building a diverse, inclusive work culture that not only focuses on our team’s performance but also our wellbeing.
How did you first discover WiDS?
I came across WiDS on LinkedIn in 2018, when it was quite new to New Zealand. The conference event was sold out. I was desperate to go, so I messaged the WiDS New Zealand ambassador, Kate Kolich, who I did not even know. She kindly replied and said I could attend. She has been my mentor and friend ever since.
Have you been involved with WiDS since that first experience?
I have never missed a WiDS event New Zealand since that first one. As my career progressed, I had more opportunities to contribute. I was on a panel discussion in 2020 in New Zealand, and again one year later in WiDS Central Eastern Europe, and this year I had the opportunity to deliver a talk.
How has WiDS made an impact on your life and/or work?
The first time I attended WiDS, I was not yet a data scientist. It was what I aspired to, but I did not have the courage to change the trajectory of my career in finance or believe that I could find a relevant job and use my skills in data science. WiDS helped me to make connections, find mentors, connect with others, and lean into this community, which is not obsessed with achievements and elitism -- quite the opposite, it’s relaxed, honest, and helpful.
What comes next for you? And what are your hopes for women in data science in the future?
I am looking for opportunities to conduct research into issues relating to families, specifically women and children in New Zealand. I want to learn more about how to bridge data science and policy making to make an impact -- I want to contribute to this goal as an executive at my workplace and an individual, and as part of the WiDS New Zealand community. I also hope to use what I learn on this journey to serve my homeland in any way I can, even if for now it is simply being part of the WiDS community in Hungary.
How has participating in WiDS impacted you? Send your #WiDStory to: firstname.lastname@example.org.