Senior Quantitative Researcher
CurrentI conduct end-to-end full cycle survey research projects using a variety of survey design methodologies and data analytic approaches. I combine rigorous survey data with behavioral data from the Slack platform to better understand customer sentiment, inform product direction, bolster product marketing, and monitor product health.I lead and monitor a daily tracking survey that constantly monitors changes in user sentiment. I built out a custom dashboard that updates the results daily. I also conducted several intensive deep dives on these data, using lightweight NLP (e.g., sentiment analyses, Term-Document Frequencies, etc) on user's open ended feedback to understand what elements on the Slack platform most strongly predict both positive and negative sentiment.I lead numerous research projects on domains that are of key importance to stakeholders at Slack. Specifically, right now I am leading end-to-end research on AI and Workflows in Slack.For over a year I lead our quarterly customer tracking survey. I designed, launched, analyzed, and shared the results from this survey on a quarterly cycle. The purpose of this work was to track and predict user sentiment towards Slack, investigate any trend changes, and provide insights to various stakeholders ranging from Slack's marketing teams to the CEO. My work here has been featured (e.g.,) in our marketing materials for various Slack features (e.g., Huddles, Clips) and for Slack broadly.I am also involved in many of our academic partnerships, conducting high impact academic research for both public dissemination and peer-reviewed outlets. The goal of this work is to better understand, and improve, the future of work.Finally, on the technical side, I have developed and maintain a small r package of custom functions that streamline our data cleaning, analysis, and visualization. My streamlining of commonly used analytic approaches into a singular package has optimized some legacy code files by more than 90%.