Trava is a mobile travel app that has simplified trip planning for over 3,000 users across iOS and Android. Users can easily create trips, vote on attractions, and receive personalized, logistically-optimized itineraries, making planning fun, efficient, and democratic.As the lead of a 5-person engineering team, I championed Agile practices to enhance feature rollout. Some of my key contributions include:• Backend: Architected a robust and performant backend using Node.js, AppSync GraphQL, Lambda, DynamoDB, and more.• Mobile frontend: Developed the mobile app with React Native & Typescript, utilizing React Query for state management and caching.• Web development: Created Trava's launch website with React & Remix for lightning quick page loads and an internal admin portal with Next.js that enabled non-technical stakeholders access to editorial data.• UI innovation: Developed a first of its kind 2D drag-and-drop interface in React Native, enabling users to effortlessly customize their itineraries.• AI-powered search: By integrating OpenAI embeddings with OpenSearch, I significantly improved the intelligence and relevance of our search system, boosting user engagement of our Explore feed by 450%.• Content expansion through retrieval augmented generation: Led the shift to AI-generated content, expanding our database from 2,500 to 100,000 recommendations, upholding quality benchmarks while reducing cost per recommendation from $25 to $0.05. These initiatives highlight my proficiency in harnessing emerging technologies to drive advancements in user experience and operational efficiency, instrumental to the growth of the platform.

As a Senior Analyst at The Cambridge Group, I played a key role in driving the international growth of a Fortune 500 technology client in the financial management software arena. My contributions included:• Devising a data-driven approach to the client's global expansion strategy, which was instrumental in identifying high-value consumers in addressable market• Designing a survey to explore 75 differentiating attitudes and behaviors among consumers in client’s addressable market• Performing k-means clustering on survey respondents to divide addressable market into 6 discrete segments of consumers• Applying linear discriminant analysis to pinpoint the eight attitudes most predictive of a consumer's segment, which empowered our client to effectively classify their user base and enhance engagement strategies.

• Developed and wrote R scripts to automate internal analytic processes, which significantly boosted our efficiency and refined our clustering solutions.• Successfully streamlined statistical clustering workflows, which saved the firm hundreds of analyst hours each year, allowing the team to focus on higher-value tasks.• Led comprehensive training sessions to upskill all analysts at the firm, ensuring widespread adoption and understanding of the new automated processes.

As the first onsite employee, I collaborated closely with the founders on pivotal aspects such as product development, growth strategies, and financial planning. A significant part of my role involved:• Designing mathematical models to strategically allocate funds across various customer acquisition channels, enhancing our marketing efficiency.• Conducting multiple regression analyses to assess the impact of four crucial engagement factors on user acquisition, which led to a revamped social acquisition strategy and a notable 22% decrease in user acquisition costs.• Identifying and prioritizing three key markets for immediate expansion, employing innovative proxies to evaluate editorial talent, competition levels, and fan base enthusiasm. This also involved tailoring subscription prices to reflect regional differences in willingness to pay.

Conducted asset allocation analysis • Revised short and long-term allocations for clients based on market forecasts• Illustrated potential asset allocation scenarios for clients looking to invest additional fundsProduced client-related materials• Composed monthly portfolio reviews providing clients with customized performance reports• Developed reports detailing biographical and financial data of prospective clients

• Analyzed the determinants of player performance to distinguish between poor luck and poor play • Incorporated experience playing baseball to transition analysis from lab to playing field• Developed ability to communicate complicated data in an intuitive manner

• Identified heavily demanded items, purchased at Black Friday discount, and sold for profit on eBay• Discovered price maximizing combination of auction features to increase ROI from 18% to 24%• Accumulated $60,000 in lifetime sales on over 700 succesful transactions