Welcome to November’s NAVBLUE Employee Spotlight Feature!
We’ve created these stories with the goal of shining a spotlight on the pivotal role our employees play in the tech and aviation field, their journeys so far, and how NAVBLUE aims to create an innovative and inclusive workforce with their help.
Today we are sharing the story of Reem Al-Halimi, AI Enterprise Architect and Data Scientist in Waterloo, Canada.
Interesting Facts
- She created and coached a children’s Lego Robotics team for three years
- She survived a war
- She enjoys giving her nieces and nephews a “special gift unwrapping experience”, with her daughter as co-conspirator: They put money inside plastic balls then superglued the covers; wrapped a gift inside many boxes Russian Doll style, with each box wrapped individually; and wrapped a chain around a gift and put locks on it, then hid the keys all around the house for her nieces and nephews to find, among many other experiences.
Q&A
–Thank you for joining us, Reem! Can you share a bit about your background?
I am a Canadian Palestinian. I have been living in Canada for over 30 years. I was born and grew up in Kuwait, and did my first couple of undergraduate years there until the Gulf war. After the war I moved to the States where I got my B.Sc. in Computer Science with a minor in Electrical Engineering from Rensselaer Polytechnic Institute, then moved to Canada where I got my Doctorate degree in Computer Science from The University of Waterloo.
-Can you tell us, in brief, what an Enterprise Architect, Data Scientist is and what that role entails within NAVBLUE?
At NAVBLUE, an enterprise architect is responsible for translating business objectives to technical problems that can be taken on by solutions architects and development teams to be developed into actual product features. In addition to this, a data scientist within the Enterprise Architecture team is responsible for ML and data activities within Navblue. This includes: identifying business objectives that can be achieved using machine learning techniques, leading ML-based exploration of future capabilities, as well as planning and leading the creation of the infrastructure necessary to support smart products.
-On November 8th we observed STEM (Science, Technology, Engineering, and Math) Day. What was it that made you pursue a career in STEM? You wanted to study something in the STEM field since you were a child?
I come from a family of engineers so I was always very interested in math and science. Growing up, my parents nurtured this interest in every way possible from helping me and my siblings excel at school by always being engaged and available to support us; to taking us to bookstores and annual national book fairs where we always came home with big piles of new books; to surprising me with my first personal computer long before computers became a common household item. It was this that got me hooked on programming, leading to my career in computer science and AI.
-Although the number of women graduating in STEAM subjects has grown in recent years, there is still a gender gap in the number of women graduating and working in STEAM subjects. As an expert in the field, do you think AI can finally close this gap?
I actually believe, if we are not careful, AI can widen that gap. Machine learning systems learn to emulate the patterns they see in the data they train on. If that data includes biases we see with the gender gap, the ML system will pick up on it and apply it to its output. This is why ML systems in which that bias is not addressed are more likely to recommend men than women for technical roles, for example. This bias is also what led to a black male being mistakenly signaled as a wanted person in the US by an AI system. But that issue is very much a focus of current research, and addressing bias against less represented groups is part of best practices for building machine learning systems in the industry. Users of AI systems also have a responsibility of always testing their systems to look for such biases, and ensuring they are addressed if found.
-What advice would you give to a girl who wants to pursue a STEM subject?
Follow your heart! If you enjoy exploring, learning, and experimenting, go for it! Do not let anyone intimidate you, and never allow negative stereotypes of girls and science affect you! If no one around you does it, you lead the way! And be yourself.. It is enough reason for you to like something to do it!
–And a woman who is trying to break into the STEM workforce?
Be persistent and strategic! Set your priorities straight at each stage in your life! I defended my doctoral thesis while 9 months pregnant, then stepped back for years because I wanted to be with my kids. That was my priority at that stage. Yours may be different. Now I have a dream job! But getting back into the work force was not easy! It took lots of searching, a continuous learning mindset, and a lot of persistence and resilience, but it paid off.
Keep at it and you will get there!
