For even more details about my experiences below, connect with me on LinkedIn.
I currently lead a team that sifts through Wayfair’s vast troves of data to identify B2B sales opportunities. This involves both identifying and prioritizing novel opportunities, and leading efforts among engineering and data science stakeholders to bring them to life.
I opted to join Wayfair after my time at Harvard, focused on growing and improving the company’s email marketing efforts. My big wins included launch of algorithmic content sorting, a new machine learning approach to email cadencing, and a better understanding of when our customers would engage most with email.
In 2016, I spent my summer building machine learning-based customer scoring models that support Wayfair’s direct mail efforts.
Between graduate degrees, I built machine learning models to support Legendary’s forward-thinking marketing and social media strategies. My work focused on understanding and predicting Twitter demographics, and segmenting Twitter users.
My work at The Times focused on building analysis-focused data systems and developing machine learning models in support of digital advertising, print circulation, social media engagement, and audience development for mobile applications.
I cut my teeth in the analytics and business intelligence spaces at Inquidia (then known as OpenBI). There, I built data warehousing and reporting solutions for clients across many industries.
See more details on LinkedIn.
My undergraduate experience focused on social sciences, mathematics, and liberal arts coursework. My efforts received scholarship recognition from the Economics department, with which I remain involved in an advisory capacity.
In my remaining time, I honed my web design and web application development skills intering at the UW-Extension and UW Colleges.
Two years ago, I completed my Master of Business Administration at Harvard Business School. Beyond HBS’s comprehensive core curriculum, my elective coursework has focused on analytics, marketing, technology, and digital transformation.
Previously, I completed a Master of Science degree at Harvard’s John A. Paulson School of Engineering & Applied Sciences in the cutting-edge CS&E program. My coursework focused on topics in machine learning, applied statistics, data visualization, applied mathematics, and scientific computing. I was later invited to TA CS 109.
