Having graduated from SPICED, Lillian is currently working as a Data Science Consultant here in Berlin. We spoke to her to find out more about what brought her to Berlin, and what she learned from her experience at SPICED.
When was it that you began to seriously think about learning Data Science?
In 2011, I briefly worked for an NLP start-up. The company was essentially trying to train a computer to read articles and automate accurate summaries based on the article’s content. Since then, working in machine learning and AI was a ‘far away’ dream. It was not until I moved to Berlin and started working in Business Intelligence that I saw that this dream could actually become true. I enrolled in an economics program and started taking classes through the statistics and wirtschaftsinformatik departments. However, it wasn’t enough. I still lacked good Python skills and a deeper understanding of how some key data science models work. SPICED was able to bridge that gap in my knowledge.
When did you move to Berlin, and why did you choose this city?
I moved to Berlin in 2013 for two reasons: I love this city and I was in love with a German dude. The relationship did not last but my love for this city is still strong.
Before starting SPICED, what were your biggest fears?
I was worried about my lack of coding experience.
How did you overcome that?
I spent a lot of my free time in the months leading up to the bootcamp doing online tutorials. I found codecademy and talkpython.org tutorials to be the most helpful for coding and pythonprogramming.net the most helpful for using Python in the context of machine learning.
What have you learnt about yourself during your time at SPICED?
I learnt that my experiences working in Business Intelligence and logistics across several industries is actually quite helpful in data science. Data science is a hot topic and companies are willing to spend a lot of money to use data science (AI/automation) to improve their business processes. However, many data scientists have very technical or academic backgrounds and may focus on solving the wrong problem. My ability to easily understand a business’ operations and target its weaknesses helps me pinpoint areas that could profit from data science solutions the most.
What was the biggest challenge for you in learning Data Science?
Due to the speed in which some subjects are covered (i.e. a day) I decided to focus on certain aspects of data science that I found either the most interesting or the most relevant. I had to come to terms that I won’t be able to master every tool, algorithm, or process in the allotted three months.
Did you have a favourite project?
We worked on a couple projects as a team. This included a Kaggle competition for sentiment analysis and developing a twitter bot. I liked these projects the most, because we were able to achieve so much more by working together, rather than independently. I, also, really liked my classmate’s final project. He developed the pphhilthy chatbot, which would tell you interesting facts from the food safety inspection results of establishments all over the Philadelphia area.
Now you’ve finished at SPICED, what are you up to?
I am employed as a Data Science Consultant at Pivigo. The company helps both businesses and individuals with their data science needs. On the business side, we work with companies to help define and solve their business needs with data science. On the individual side, we help people who have recently completed or are near completing their PhD or doctorate in the sciences transition to data science. Those who have completed our program often go on to work on one of our client projects; which, in turn, can lead to full-time employment.
What advice do you have for people who are thinking about studying Data Science at SPICED?
Don’t be afraid and keep an open mind. You can learn an amazing amount in just three months, if you are willing to.
