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Work Background
DoorDashProduct Analyst
May. 2024New York, New York, United States* Built a Tableau dashboard to track Global Search Metrics across New Verticals. * Created insights around experiments for new vertical product features using SQL.
The ZebraSenior Data Analyst
May. 2023 - May. 2024Supporting growth/lifecycle marketing efforts by leveraging both marketing & customer data in order to improve customer acquisition & retention.
UberData Analyst
Dec. 2020 - Feb. 2023San Francisco Bay AreaAnalyzed the behavioral patterns of Uber’s customers across both lines of business. Wrote and maintained queries using Presto DB to manage audience sampling and ad-hoc requests for marketing intelligence.
• Developed a clustering model that drove gross bookings and first trips across key Cornershop markets, resulting in a 21.8% lift in gross bookings and a 9.91% lift in first-time adoption
• Created a metric to define Uber Important Customers (UIPs) that product and engineering teams used to categorize high-value customers in the data warehouse.
• Segmented users across different verticals (Micro-mobility, Membership) to differentiate the value of customers within Uber’s ecosystem.
• Built dashboards to track a wide variety of business interests, including active users, new vertical growth, and driver earnings
KasasaData Analyst
Aug. 2020 - Dec. 2020United StatesMember of the Research & Insights team
* Built and deployed performance dashboards in KNIME to measure prediction accuracy of machine learning models in production. * Improved accuracy of a machine learning text classifier through text pre-processing and analysis.
University of Colorado BoulderAnalytics Consultant
Jan. 2020 - May. 2020Boulder, Colorado, United StatesHunter Douglas
•Analyzed Window Shade product data to predict the probability of early product failure using R & Python. •Performed Exploratory Data Analysis, Cleaning, & Transformation to prepare the data in a model ready format.
•Built, reiterated, and tested machine learning models to identify the most accurate predictions for product failure. •Provided recommendations to the company on implementing a model that most accurately predicts future orders. Seagate Technology
•Analyzed hard drive data using Python & R to predict the probability of a hard drive becoming a failure before the first stage of testing in the manufacturing process. • Built, tuned & refined Machine Learning classifiers to accurately predict the amount of hard drives that could be potential product failures.
Tata Consultancy ServicesIT Consultant
Mar. 2017 - Jun. 2019Pleasanton, CADeveloped product roadmaps, executed disaster recovery analysis, and charted testing and planning strategies for PeopleSoft upgrades.
• Designed weekly and monthly IT Change Request ticket management dashboards using Excel
• Delivered a new intake form for IT tickets using Microsoft forms to automate emails using Microsoft Flow
• Collaborated with business and security teams to deliver a modern, customized UI for pilot users as part of the
scheduled Kaiser release cycle
• Created project scope presentations to provide data visualization on testing efforts and metrics for each release cycle
First Tech Federal Credit UnionMarketing Intern - Digital Analytics
Jul. 2016 - Dec. 2016Mountain View, CA• Organized the Credit Union Analytics Summit 2017, a large conference with 400 + executives that focused on the use of Data Analytics & Business Intelligence within Credit Unions. • Drove web traffic to the Summit website by sending scheduled email campaigns to top finance executives across the nation. • Participated in Agile/Scrum Ceremonies (Sprint Planning, Sprint Review, Sprint Retrospective) and used JIRA for managing user stories and tasks related to Summit organizing. • Communicated with Marketing Managers & Directors through emails and phone calls & signed up software companies to become sponsors at the summit.
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