It was a very good decision to take Ubiqum's business data analytics course as it allowed me to make the professional change I was looking for.Alumni Story: Neus Montserrat
When did you enroll on the Data Analytics & Machine Learning Program?
I started in April 2017 and had already received a job offer by the end of September.
Where did you get hired and where are you working now?
Since Ubiqum, I’ve been working as a business analyst at Sogeti and give service to HP. Currently, I’m working on a project for HP large format printing in the Customer Success team. It means working with very different kinds of data in order to provide useful reports to, for instance, the account managers, so they can help their customers understand how they are performing with their printers.
What were you doing before you signed up to Ubiqum’s Data Analytics Program?
I was working as a project manager and analyst in a marketing agency when I found out about Ubiqum’s data science bootcamps. What I liked most about the program was the “Learn by Doing” methodology, the topics looked at on the program, and the tools that you learn to use, which all focused on preparing the student for the workplace and making them highly employable.
I had an interview with Ubiqum’s founder, Sebastián Barajas, to see if it could be the right course for me. After the interview, I was totally convinced that it was the professional change I was looking for and decided to quit my job so that I could start the course and find a new job related to data analysis.
What’s your educational background?
I studied Business Management at Pompeu Fabra University (Barcelona) and Research and Marketing Techniques at Universitat Oberta de Catalunya (online).
Do you feel your original background and data analysis are related? If so, how?
Yes, they are.
In my previous jobs I had always worked with data: financial data, marketing campaign data, sales data… However, I had never used any kind of specific tool or algorithm to analyse it, instead, I used Excel to do my analysis. I have always been involved in projects that required data analysis but I didn’t have the knowledge to do it with the right tools, and therefore efficiently.
My previous experience in marketing and business helped me a lot. In data analysis you first need to formulate the business questions, then analyse the data to get insights, and finally go back to the question with a non-technical response (most of the time), so I was quite good at that!
What makes you most passionate about the world of data analysis?
I have been fortunate enough to enter a newly created department and the need for data is very large, so any insight we can contribute is used and serves as a great decision maker. You feel that you are a key part of the team and are involved in many of the important decisions.
How did you decide to attend Ubiqum? What made it the right program for you?
I was looking for a full-time program (9 to 5) with a focus on working on real business cases, not only equipping you with the technical skills, but also putting you in real-life scenarios as a data analyst. We did a lot of role playing, worked on our presentation skills, learned the importance of storytelling when doing presentations and how to handle a business question, gather insights from data, and return with a business recommendation based on our findings.
I liked the fact that other students came from different backgrounds (engineering, physics, sales…) as this enriched my experience; I could see different ways to approach the same dataset or problem through the many perspectives my colleagues offered.
What are some of the data projects you’ve worked on in your job?
I’ve been testing different tools that apply natural language processing and sentiment analysis to customer feedback to choose the best option and implement it in HP.
I’ve created dashboards in Power BI, automatised analysis with R scripts, and created reports containing metrics related to efficiency. I’ve also done a revenue and profitability analysis for some of our customers and predicted future profitability.
Have you faced any challenges trying to become a data analyst?
For a profile like mine, one of the main challenges has been to learn to program in R. My mind was not used to working with code so this was the part I had to dedicate most of my time to.
Where do you see your career heading in the next 5–10 years?
I will continue studying on my own and learning about what the market needs. I plan to specialise in Big Data or become a data scientist.
If you could go back and give yourself one piece of advice before pursuing this career track, what would it be?
Maybe not to wait so long in deciding whether to start the course, since it was a very good decision and allowed me to make the professional change I was looking for.
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