05 Nov 2021 Aspire to Tech – Senior Data Scientist at Charli AI
Career Spotlight – Nazanin Hamzei
What is your role? What is your title? Where are you located? How long have you been doing it?
I am a senior data scientist. I have been with Charli AI for two years, but I was doing data science for two years before that, so four years in the data science industry. I live and work in Vancouver.
What makes your job interesting?
There’s an analytical side to my role, and the interesting fact about that is, I use data. Data is very impartial and very objective. You use data for getting insights and making informed decisions. On the machine learning side, what makes it interesting is that you build a system that can generalize beyond hard coded logic. This is an impressive technology to have, but you can also learn from users’ behaviors. It can evolve and change as time goes on. As more users, use the product, it can tailor itself to users’ needs. I find that fascinating.
What is the most fun? What is the most challenging?
As scientists, we have to constantly stay up to date with new technologies, new paradigms, and new solutions to those paradigms. This is never ending but it’s both fun and challenging at the same time.
How does your role help drive the company’s success?
At Charli AI, embedded AI is one of our advantages over our competitors. Charli AI knows the difference between invoices and contracts. It can learn how to pull the most relevant pieces of information for better organization and findings. This is one of our core values, and I think is going to continue to drive us forward. Our AI capabilities give us a competitive edge over our competitors, and that is what I help contribute to the team.
What does a typical day look like for you? What do you actually spend your time doing?
A typical day would involve researching or coding a solution for a specific problem. I spend time writing algorithms used for tasks like extracting people’s names from a document page. I train a model or write algorithms in order to do that, that is what most of my time is spent on. I typically also have meetings during my workday that take about an hour. They can be company-wide meetings, or they can be with specific teams like the engineering team. We spend time discussing problems and solutions or future directions within our data science team.
A portion of my time is also dedicated to mentoring and coaching interns. This is something that I want to spend more time on in the future. I spend time giving them directions and resources, troubleshooting, and giving them advice on how to complete their tasks. It’s good to have a fresh mind to look at things and it’s rewarding to be able to teach them.
Tell us about your career history?
I have a master’s degree in electrical and computer engineering. My final master’s project was focused on brain signals. I studied a data set of brain signals collected from the brains of people, while they were working, to mine the data for patterns. That led me to a company called Neuro Catch Inc., based in Surrey. They were a startup at the time. They had two medical devices, both related to the brain. One was for monitoring brain responses and the other was just a consumer grade device. I was working as a software specialist and trying to introduce machine learning into their products, but it had its own challenges. For example, in medical industry most of the time data is very expensive to get, which poses an inherent challenge for machine learning approaches. That’s why I transitioned to my next role which was with General Electric Digital for about a year. And this is where I met some of the people I now work with at Charli AI.
What was your very first job and how did your career path take you to where you are today?
The first job was with Neuro Catch Inc. I was always trying to find that sweet spot between data science, data processing, and data mining in general. For specific applications in the medical industry, the use of machine learning is very limited because of the lack of data. That’s why I transition to General Electric Digital in order to have more free access to data and be able to practice what I learned with real industrial data. Unfortunately, shortly after, GE Digital was closed down and the whole office was laid off. That is around the time when Charli AI was founded. We just wanted to start over, and we were all happy to be part of this new company – That’s how Charli AI was formed.
Where might you go next? What motivates you for the future? Will you stay in tech?
For my next role, I’m either looking for a more senior role, where I can practice and enhance my leadership skills, or a similar role like a senior data science and machine learning position where I can expand my technical skill set. If I stay in a similar role, I want to work with different modalities of data, and work with bigger datasets, in bigger teams and experience new ideas. I would like to work with more state-of-the-art technologies. I will probably stay in data science and tech – unless I have a midlife crisis that prompts me to go study ecology and save the environment!
In terms of motivation, we are immersed in data, nowadays. Every second new data is being produced and added to the already huge pile of data that we have on the Internet. Making sense out of this huge pool of data and turning it into information that can be usable for humans and computers alike is the way forward. Data is becoming a universal language and I’d like to be fluent in it. That’s what motivates me for the future. The possibilities are endless.
Any final words of advice?
If I have one piece of advice to young professionals, it would be to map out your personal mission and find what is important to you, according to your traits and your own core values. Then, make sure that they align with your company’s mission, and what you’re striving to achieve. The benefit of this is that it gives a whole new meaning to the work that you do, whether its trivial or non-trivial. Thinking about it this way, gives your work a whole new meaning.