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Robyn’s Career Change: From Finance to Data Analysis

Attracted by analytics and the top, in-demand careers, Robyn had one objective in mind: to become a data analyst. After nine years of working in finance, she took a leap of faith and challenged herself by enrolling in the data science bootcamp. Read about her journey below, including how she accomplished her goal.

What was your professional occupation before Le Wagon? 

Before Le Wagon, I worked in finance for nine years. I started as an Investment Assistant in wealth management and worked my way up to become an Investment Advisor.  After reaching my goal of becoming an Investment Advisor, I quickly learned that this was not the career I wanted for the rest of my life.

What inspired you to learn data science?

At that point, I realized that analytical work is what I enjoyed the most. I met with a career advisor, who sent me an article about the best careers for the future, and I found out that there are great job opportunities in the data analysis sector, so I decided to give it a chance! 

I started doing informal interviews with people working in the field and enrolled in SQL courses. I knew right away that this field matched my interests. I like that data analysis bridges the tech side with the rest of a company, and that you need excellent communication skills to be successful. 

Why did you choose Le Wagon to help you change careers?

I tried to enroll in a master’s program, but I needed a high-level education in math or computer science to get into it. With that in mind, the bootcamp turned out to be a good solution. I chose Le Wagon because it has high recommendations across the world. 

What’s more, I thought it would be interesting to learn data science because it’s a step above data analytics in terms of complexity. I felt it would help me get the type of job I pursued and learn Python more fluently, which is a must-have skill in the data industry. 

What did you think of your bootcamp experience? 

It was intense! The amount of skills that I learned in such a short amount of time is quite remarkable. 

I found that having challenges every day was a great way to learn. It helped me hone my skills to develop and write in Python more naturally. I also really enjoyed the project weeks, which allowed me to develop my ideas and see the concrete results of my hard work! 

How was your job search after Le Wagon? 

My strategy was to send as many applications as possible in order to get interviews and start practicing. 

On top of sending applications, I reached out to people working at the companies I was targeting and sent them a link to my demo day pitch. I found that adding a personal touch to my applications helped a lot, and I landed a few interviews through that method. 

What’s your role at Psycho Bunny? 

Psycho Bunny is a men’s clothing company founded in New York and based out of Montreal. It’s a company that is growing quickly and is building its data team. 

In my day-to-day, I make sure that the data is clean, and I run analysis to answer questions such as “What % of our customers are coming back?” or  “What do new customers usually buy?”. 

Right now, we’re working on building a data lake. We are creating one centralized source of truth for the data that exists across various systems and applications.  

In my day-to-day, I use SQL, Excel, Python, and data visualization tools.

How do you use the skills you learned at Le Wagon?

An important thing that I learned at Le Wagon is doing research and reading through the documentation.

Doing tasks I’ve never done before doesn’t scare me now because Le Wagon taught me how to look for the information I need.

Someone has likely done this stuff before me, so I know I’ll find the answers on the Internet by using the right keywords. I really like that most things are open source in the data industry! 

These are essential skills to have because I need to be self-sufficient in my job. I am given high-level goals, and then it’s my responsibility to figure out what to do. 

Any advice for those who want to get into data analytics? 

Continue to code after the bootcamp! Don’t forget that learning to code is like learning a new language: You need to practice if you don’t want to lose it. 

If you want to pursue a career in data analytics, you need to master SQL and data visualization, so keep working on these skills! 

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