Women’s History Month: Celebrating Caribbean Women in Data with Arielle Khan

It’s the last week of Women’s History Month and I just had to do something to celebrate! As a woman in data, I think it’s important to connect with other women like me, but I also think it’s important to show others the diversity in data professions. You could be an analyst, an engineer, a scientist, and much more. Data professionals also work in different industries and solve a plethora of problems and I hope to underscore this with my Women’s History Month posts. This month I reached out to a number of women in data who are of Caribbean heritage, and I’m excited to share about them, what they do and their advice to other women and girls who are interested in working with data. This post is a short interview and spotlight feature on Arielle Khan, a full-time Software Engineer and part-time student pursuing a M.Sc. in Information Communication Technology. Arielle is from Trinidad and Tobago and has worked as a Data Analyst in the past. She is currently pursuing academic research in Machine Learning and AI at the University of Trinidad and Tobago.

How would you describe yourself?

My name is Arielle Khan and I’m a 25 year old software engineer who believes in living a full, well-rounded and meaningful life which balances career with other priorities. Ten years ago, in a high school coding class, I discovered my passion for the field of technology and I am beyond grateful to have since immersed myself in that field while also pursuing further education and hobbies such as pageantry, travel and dance.

How have you used data to solve problems at work, school or in everyday life?

Data is one of the most powerful decision making tools we have at our disposal. In my last position as a Data Analyst, I was able to provide insights to executives and other stakeholders that helped them gain a deeper understanding of the business and help drive decision making. I am truly humbled to have been able to play a part in assisting these distinguished professionals perform their duties and as IT professionals I do believe our major role is one of service and support through innovation. 

How did you get into the data world?

While working as a developer, there was a gap in filling the reporting needs of my department. I got the opportunity to work with a vendor that provided business intelligence software. Once we discovered that custom reporting was possible on this system, I threw myself into learning how to build custom reports and visualizations on the platform. Eventually, I was promoted to the position of Business Data Analyst, a position that did not exist before. Sometimes you don’t need to take an opportunity, you need to make one.

Why do you think working with data is important?

While I’m no longer directly working in the data field, as a software engineer it’s still closely tied to my role. Data is not going anywhere. Its influence will only keep increasing as we discover more sophisticated means of storage and processing. I am looking forward to contributing directly to the field through research pursued for my masters degree, which will be focused on machine learning and artificial intelligence.  

What suggestions would you give to other girls/women who are interested in getting into the field?

My advice to other women looking into getting into this field is to never stop learning. The field is so dynamic that you really do need to form a passion about it and be excited to discover what’s new to keep competitive. If you can find a niche and find ways to make yourself stand out, I think this field will continue to have a lot of fantastic opportunities. The general career advice I would give is to not force yourself to like something. Not everyday is going to be roses, but loving what you do paired with practical skills will get you through even the toughest days. Always remember that you’re more than your job title, but a fulfilling career can play a part in a fulfilling life.

Today we celebrate Arielle, cheer her on as a Software Engineer and look forward to her discoveries in Machine Learning and AI!