Work Experiences:
I am currently working as a Data Science Intern at System2 LLC, a company based in Manhattan, NY that offers sourcing, engineering, and analysis of big data as a service for hedge fund companies and private investors.
During my time here, I had the honor to take on several projects from beginning to end. I would have weekly meetings with clients to understand their investment questions (e.g. how well/fast can xyz company recover from the global pandemic), I will then turn that into something measurable - usually by performing both qualitative and quantitative research and assessment on the company’s KPIs, and choose the most predicative and informative KPI to use for the forecast, I then collect and prep the data, analyze it - by comparing models, fine-tuning model parameters, and testing model enhancements, and present the takeaways using a client-facing, interactive interface that can help clients best visualize and understand the investment implications of my forecasts.
For me, the most rewarding part of being a Data Scientist is that there are almost no limits to the kind of problems I can take on. I am able to turn data into qualitative information that can be used to inform various business problems.
During my undergraduate career, I was also actively involved in computational psycholinguistics research. I studied and challenged the concepts behind human communication and cognition and improved existing studies and generated effective new studies through collaborations with faculties and other researchers. Combining my knowledge in the field and my data analytics skills, I translated problems and ideas into valid study designs and data models, and then back to forms deliverable and comprehensible by audience in various settings. My honors thesis, titled “Individual Visual Statistical Learning Differences as a Predictor for Language Processing”, inspired by my involvement in the field, bridges the gap between human visual perception and language skills.
Through research, I was not only able to see the power of data, but also see my own ability of transforming data into actionable insights.
