The last Jump Start Data Science Alumni Meetup was with Ben Arancibia and Jasper Lu.
Mr. Arancibia is currently working at a pharmacutical company, GSK, which is based in the UK. He graduated from William and Mary in 2011 as an international relations and environmental policy double major, though he focused on the tech side (economics, stata, GIS) of both of those majors. He went straight into the workforce after graduated as a GIS analyst but later recieved a graduate certificate in GIS from VCU and a got a masters degree in data science from CUNY. At the start of his career Mr. Arancibia worked mostly in the field of GIS but later he moived into management consulting. Currently he is working to implement machine algorithms for business-use data (meaning he spends a lot of his time sifting through data and trying to figure out how to best communicate his findings.)
Mr. Lu is currently transitioning between jobs though most recently he was working as a data scientists at TripAdvisor. Mr. Lu graduated from William and Mary in 2011 with a double major in economics and mathematics. He then immediately went on to get his masters degree from Boston University and found that his math skills weren’t as strong as he had thought and also that he did not want to work in finace (it was too cut-throat). He started off working as a pricing analyst at Liberty Mutual, but he found that insurance was too slow-moving and regulated. As a result he decided to move to a startup (Wayfair) which allowed him to work with lots of different groups within the company. After a few years with Wayfair he moved to TripAdvisor but was laid off due to the Coronavirus crisis. Luckily he found another job at Shopify, but he was able to provide us with valuable insight into the job market during this pandemic.
Both Mr. Arancibia and Mr. Lu provided us with valuale advice and insights into the data science field. They described the typical interview process in the field of data science and impressed upon us the fact that companies are most interested in discerning how we are able to think critically and work through a project. Both encouraged us to know a coding language well and get as much expercience/practice with data science projects as possible (either through internships or things like Kaggle competitions) to help us stand out in the job market. They also highlighted the importance of networking when trying to find a job (as all of the other alumni have done as well).
There were three insights that I found to be especially valuable for myself. The first was that Mr. Arancibia mentioned that in the field of data science “how well you solve a problem is a reflection of how good you are at googling a problem.” Secondly, Mr. Arancibia also mentioned that he moved away from GIS into more machine learning because once he entered the workforce he realized that GIS wasn’t everything, but rather that it was just one tool in his data science tool belt that is available to him when he is trying to solve a problem. This was especailly important to me because GIS/ cartography is the field I think I want to go into. Finally, they shared with us that when we are searching for a job in data science that knowing what type of data science you want to practice, how to communicate your results and how to make people care about the data analysis you are doing are of the utmost importance when it comes to succeeding at finding a job and later succeeding at a job.