Main focus: data-driven decisions
Twitter handle: @jill_augustine
Languages: English, German
Topics: communication, education, data analysis, machine learning, data science, ai, diversity and inclusion, dataviz, stem education
I am a data scientist and question answerer. I received my PhD in Molecular Biology from the University of Vienna (Austria) and my BSc from the University of Leeds (UK) during which I also studied at McGill University (Montreal, Canada).
My main interest (and the reason I became a data scientist) is using data to answer questions regardless of the industry. I have experience working in the telecommunications industries. In particular I am passionate about data understanding and communication both to stakeholders and within data teams. My professional approach to data science is to use the tool that gets the job done given any constraints from team members and stakeholders.
Another interest of mine is increasing the inclusivity of working groups through open exchanges and active diversificartion. I try to make my presentations are accessible as possible and welcome feedback as to how I can improve this further. I welcome opportunities to speak about my work at conferences and meetups. Please get in touch through Twitter or LinkedIn if you would like to know more.
Examples of previous talks / appearances:
When I tell people where I work and what I studied, the response is always one of surprise. If you were to say that molecular biology research and telecommunications data science have nothing to do with each other, you’d be right… but also wrong. In my talk I will share with you my take on careers and answer some of the career-related questions that are often posed to me on this topic.
I will talk about my transition from academia in the life sciences, into the telecommunications industry, and my experiences along the way. I will introduce you to the world of data science at A1 Telekom Austria, how we manage and protect your data, and how we use it to improve the user experience of our customers. Using examples from my current day-to-day work, I will show you how the two worlds are more similar than you might think.This talk is in: English