About this Position
FiscalNote is seeking an experienced Software Engineer to join our FactSquared team within the Data Science & AI Research department. You'll help scale & improve our end-to-end capabilities by designing, building, & supporting services for ingesting, storing, augmenting, analyzing & serving data. You'll work closely with our researchers, designers, & engineers to define performant solutions to complex open-ended problems using various natural language processing (NLP), Machine Learning (ML), & Information Retrieval (IR) techniques, build light-weight applications, & play a critical role in delivering them to the thousands of organizations that depend on FiscalNote.
About the R&D Team
The Research & Development (R&D) Department at FiscalNote is where the magic happens. The Department includes the Product, UX & Design, Technology, & Data Science & AI Research Teams. These teams work together to develop & deliver solutions to FiscalNote's clients. The FiscalNote FactSquared team builds statistical, NLP, & ML enabled services for intelligent data aggregation, manipulation, augmentation, & generation. Our team has a wealth of diverse life & career experiences that allow us to think outside of the box & ahead of the curve. We enjoy ending meetings by discussing our favorite theorems or nitpicking the latest news article on political models. You'll get the opportunity to work at an institution pushing the boundaries of open data transparency, while collaborating with some of the industry's brightest engineers & data scientists to devise, nurture, & implement cutting-edge solutions to continuously evolving engineering obstacles.
You thrive in collaborative environments in which the free-flow of ideas serves as the catalyst for bold results. You ground your work in software development frameworks while creating solutions that deliver the best results for user experience.
You're comfortable around ambiguity with a high degree of autonomy, & are excited about solving complex, open-ended problems by distilling the complexity as simply as necessary to build or adopt solutions that work. Along the way, you're comfortable communicating what you're thinking to both technical & non-technical audiences, taking in others' ideas as well as expressing your own.
You readily solve problems by applying statistical solutions & systems thinking, especially leveraging NLP & ML tools, & are excited about productionizing off-the-shelf solutions as well as experimental code to push the bounds of people's expectations.