October 29, 2019
At gk we’re proud to champion diversity and inclusion. Our team and company culture represent top talent from diverse backgrounds. We’re particularly proud of the number of women we have in senior and specialist roles, as we know the ratio of male to female employees can be an ongoing challenge for many tech companies.
With this in mind, we put the spotlight on Amy Geojo, Data Scientist at GK, to share how she got into the field of data science and what she enjoys most about her role.
Amy, tell us a little bit about you and your background.
I’m at Data Scientist at gk. I’m based in Chicago and have been working with GK since April 2018. I have a Ph.D. in Psychology from Harvard University which focused on psycholinguistics and cognitive science. The focus of my research was language acquisition and processing, more specifically syntax-semantics mappings – this is one of the many reasons that my background is particularly apt for the work we do at gk!
How did you get into the field of Data Science?
Many aspects of what comprised my doctoral research overlaps in ways with what one does as a data scientist. For example:
- Formulation of questions and creative ways to approach problems
- Development of systematic experiments
- Writing programs to create products of value – albeit their nature differs – and analysis of findings
I also gained programming experience through grad school. I conducted experiments and analyzed them which made me realize that I actually found that component very appealing and satisfying – the creation of something tangible and the myriad of ways via which one could go about doing so –piqued my interest further.
What’s more, I also took a computer science course at the Massachusetts Institute of Technology and absolutely loved it!
How did you first hear about gk? What made you want to work here?
I first became aware of gk via a recruiter and was particularly excited about the firm because the type of work we do, and the actual Natural Language Processing (NLP) product itself, are so closely related and relevant to my background in terms of my Ph.D. and subsequent experiences. For example, my early experience in data science involved working with a startup using various text sources, NLP and machine learning for predicting financial market-related ventures.
I was drawn to the role because it entailed NLP and machine learning, as well as the opportunity for more software engineering experience, which is quite a unique niche within the overall data science space.
What’s more, my initial interview was incredibly positive – I loved the people I met and I ended up remaining for a long while after my interview, just freely speaking and exchanging ideas with people in the team. The people with whom I work remain a major part of why I love gk.
Tell us about some of the projects you have worked on at gk so far
- I have evaluated Acoustic Speech Recognition, or ASR models
- I have mapped accent coverage of our models. For example, how well we do at speech recognition for native speakers of different languages across the world as well as within the US.
- Auto-alignment of audio and text – I was given a transcript and an audio-file, and I developed a method to automatically identify the times at which parts of the transcript were spoken.
- I worked on our intent classifier development to classify transactions and products.
- Chat interpreter development for specific financial domains. For example, interest rate swaps, high yield bonds and emerging market bonds to auto-extract financially relevant data from chat. This entailed acquiring domain specific knowledge and working to integrate chat and voice data streams.
What do you enjoy most about your role at gk?
I love the autonomy we have to work on projects. We are given interesting problems and the opportunity to really take ownership and identify ways to solve those problems – all while having a great support system, working with highly experienced people with fantastic opportunities for mentorship and collaboration.
Do you have a mantra or a favorite quote?
Yes, ‘colorless green ideas sleep furiously’ – composed by Chomsky. It illustrates the independence of syntactics and semantics. It’s actually a pretty significant concept. Even in niche domains, such as specific financial sectors, the same concept/component (meaning) can be expressed via many forms and the same form can be used to express many concepts, and the rules that govern the way meanings and forms can combine are distinct. Acquiring syntactic and semantic rules and forming the appropriate categories for each system is fundamental to learning.
gk is currently looking to grow the Data Science team. What would you say to prospective candidates?
Yes, that’s right, we’re looking to grow the team! I would say gk is a great place to work. Successful candidates must be able to work autonomously but also be cooperative. People share some great ideas and we have an open atmosphere where you can express yourself. The team is awesome, we’re from lots of different backgrounds and have different expertise. There is certainly the opportunity to grow, develop, learn new things and work on really interesting projects.