Women In Data Science: Martina and Gabriela
This is a piece by Brainster, a platform for education helping you future-proof your career.
The Data Science Bootcamp group just finished the Stats & Maths module. After 6 weeks of solving problems, they are entering a process of integration of everything learned so far and they are getting ready for the transition into the Python module. Before closing up the ‘business’ part of the program, we asked for impressions from the students about their experience so far.
With their long term experience in the financial and banking sector, Martina and Gabi turned out to be a perfect fit for the Bootcamp and they adapted very well to the dynamics and the challenges of it. They showed a great performance at the Business Intelligence, Statistics, SQL, and Data Warehouse modules so we talked a bit about everything upcoming at the Bootcamp, their expectations related to it, and their plans for the future.
The enrolment of the next Data Science Bootcamp is already open. Book your spot on time and hit it off with a preparatory program until the start of the Bootcamp program.
Firstly, tell us a word or two for yourselves. Where did the motivation for Data Science come from?
Martina: Analyzing data and dealing with big databases are part of my everyday work routine. Growing professionally and developing my analytical skills during my 13-years long experience in working in a bank I came to a point where I needed to learn and start using more advanced tools for analyzing and interpreting data. Most importantly, I needed tools and knowledge for foreseeing trends. This is the reason why I decided on Data Science as a career development field. The idea was in my head for years up until I met the Brainster team. At that period they were preparing the Data Science Bootcamp and it turned out to be exactly what I needed.
Gabi: My enrollment in Data Science was an act of pure inspiration and spontaneity. We talked with Martina about the Bootcamp that Brainster is preparing and I knew I needed to do it in order not to go through a professional stagnation. In my opinion, it was the single logical continuation of a 16-years long practical experience in finances (accounting, financial reporting, analysis, and planning) in times of fast tech development. I believe it is one of the best decisions I’ve ever made.
Data Science became a necessity in the field of Finance through the Business Intelligence domain. Considering that both of you work in this field, is it important to have BI skills at your job at this moment?
Martina: If there are big databases, there is also a necessity for BI. Having these skills in your skillset is of huge importance for fast and quality processing, analyzing, and visually representing data. The usage of BI enables us to react fast to market changes and anticipate them.
Gabi: The institutions working in the field of finances use data from their own bases as a tool. That allows them to conduct overall analysis, identification of risks, efficient reporting, product design, campaigning, etc. The single-use of BI makes everything aforementioned possible in cases of huge data amounts that are generated on a daily basis.
Besides the business aspect, at the Bootcamp you’ll dive deep into Python, Machine Learning, and Big Data. After finishing these modules, what are your ambitions in terms of their application and the career opportunities that arise from them?
Martina: For me, that precisely is the biggest challenge. However, I’m hoping to master these technologies considering that we are already into calculus, statistics, probability and those are the basics of Machine Learning. Also, the ability of the instructors to present the knowledge in a simple and understandable way gives me the right to have higher expectations for these modules.
Applying these technologies in your work is a big step towards building models and algorithms. One challenge here is the building of predictive models which allows you to be the change-maker on the market.
Gabi: In Machine Learning, in order to draw a conclusion from a certain dataset you need the statistical and maths methods that we are currently studying. The classes until now are empowering me that I’ll go into the new challenge pretty well prepared.
Using Machine Learning to economy data is something very close to me considering my long-term experience in financial analysis and predicting future trends. It is said that with the help of Machine Learning the economy data can be turned into money. And it seems like it’s true since the companies using it manage to increase the customer level while decreasing operational costs.
What would be your primary focus of work after finishing the Bootcamp.
Martina: Right now, my focus is on handling challenges brought by the Bootcamp itself. Our experience in the field of Finance & Banking helps us to recognize all fields where Data Science can be applied.
On the other hand, the broad usage of it in a large number of industries will be a motivation for research of new opportunities where I’ll be able to contribute significantly.
Gabi: For now, it is logical for me to help out the company where I work to keep on track and assure competitive advantages. I’m planning to apply the Data Science methods to the data the company owns. Economy data is my comfort zone. But, I’ll let my curiosity lead the way and explore other fields. Over the past few years I came to the conclusion that succeeding in a new field of work does not have to be hard, the only thing needed is a change in perspective.
The wave of digital transformation that became a necessity these last few years, is a result of applying Data Science and automation of the process. If you go back in the days, what is the advice you’d give to yourself in order to get ready for this period that is coming? That would also be advised that it is applicable for the new generations.
Martina: Another necessary thing regarding this and all new technologies is the open mind. The soonest you apply them in your work — the better the outcomes. It is evident that sooner or later everyone would have to implement it
Gabi: Data production is constantly increasing. The databases hide valuable information. If used properly, you can identify new opportunities, implement smarter business activities, optimize processes, accomplish more profit, and make customers happier than before. For this to be done in a fast and smart way, you need to use Big Data Analytics. Using Machine Learning can get the most out of Big Data and anticipate future trends. Therefore, my advice would be to use all the tools that provide minimal time for extraction and processing and more time for new ideas, suggestions, and solutions.
How are you doing at the Bootcamp? Impressions, challenges, expectations?
Martina: Excellent lecturers, well-designed program, coherent and interesting group of participants. I’m happy to go to class each day when I have one.
Gabi: At the Bootcamp I got what I wanted — a lot of knowledge simply conveyed by professionals in the field. Lots of information, new insights, different approaches, dedicated work, a lot of completed assignments, learning in class, and at home, but I have the feeling that I’m doing the right thing. I expect (I want and I believe) that I will stay maximally focused on the Bootcamp. The real projects will be a challenge, but in the spirit of constant self-challenge, I am open to new experiences.
What is your message for anyone considering career development in Data Science?
Martina: I would encourage anyone who primarily has a desire for continuous learning, has analytical skills and sees a challenge in solving complex problems to focus on Data Science. Of course, mastering this discipline requires a lot of dedication and hard work, but I think you will gain skills that are relevant and highly valued at this high level of technological development.
Gabi: Data Science is a profession of the future. So don’t wait for perfect circumstances or the right moment, don’t let others convince you, find out for yourself what valuable contribution you can make to companies and society as a whole by studying Data Science. The great news for people who want to enter the field is that Data Science has tremendous prospects for developing over the next decade.
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