Rita Lo Email & Phone Number

Bellevue, Wa, Us

San Francisco, Ca, Us

Building Lyft's AI + LLM Platform

San Francisco, Ca, Us

• Led analysis for optimizing service areas in 5 key markets, putting Lyft in a stronger position to improve wait times + acceptance rates, meet legislative and compliance requirements, and realized $750k in annual savings.• Worked with the EDU team to develop strategies for growing partnerships. Analyzed ride balance on campuses from different time and geographic dimensions, and segmented event vs. non-event riders to understand how students use premium and primetime products. Brainstormed program parameters that helped secure our largest EDU RFP, bringing in $7.5M annual spend.• Migrated airport market share data from a Google Sheet to a dynamic Mode dashboard. Created reusable logic for analyzing internal data and future-proofed data collection methodology for external sources (e.g. OpenData, FOIA requests).• Designed analysis to understand whether increasing throughput inspection locations can influence demand. Findings allowed GlobalOps to expand inspection services, and better manage third party sites to avoid cannibalization of Lyft's services.

San Francisco, Ca, Us

• Converted manual forecast into an automated pipeline that writes directly into Amazon S3. Reduced 10+hours of manual maintenance time per week while improving data accuracy by eliminating human errors. Created a reusable and scalable framework that increases refresh cadence from fortnightly to daily.• Designed, ran and analyzed experiments (time-split) to incrementally test the impact of changes in the marketplace.• Trained, optimized, and tested different ML algorithms (neural networks + regression and classification) on large ride volume datasets to create a model that serves as the basis for Lyft’s Tiered Queueing product. Explored ML libraries (e.g. Scikit-Learn, Prophet) and performed research to ensure design follows modeling practices. Developed monitoring tools and deployed data/model pipelines to bring research to production.• Deployed production-level code that is scalable, maintainable, and efficient in Python and PrestoSQL, while engaging in collaborative code reviews to gain technical feedback and improve model performance. Worked closely with analysts, project managers and functional leaders to communicate business impact.

San Francisco, Ca, Us

• Developed a dashboard as the source-of-truth monitoring the ROI of in-person customer service. Track CSAT scores, handle time, work categorization, and agent utilization, providing insights for personalized coaching opportunities with agents that improve customer experience and increase Mid-Atlantic CSAT by ~20%.• Wrote Python web scraper to automate data collection and cleaning, reducing manual touch points needed to surface monthly service and maintenance savings for our rental fleet.• Led data investigation to identify top reasons for driver non-compliance, as well as markets with highest infraction incidents. Identify low hanging root causes for regional teams to mitigate, increasing the number of road-ready drivers available for resurrection outreach by >40%.• Negotiated partnership between Clerkie.io and Lyft to roll out a pilot in the Mid-Atlantic - with the goal of offering ~6K drivers a free way to lower debt and manage finances - to result in debt reduction of $14M+, and total driver savings of $4.6M+.• Created mentorship training curricula for our Community Associates (CAs), with a pathway to expand it into a program that increases technical competency, strategic decision-making, and career pathing for CAs in the Mid-Atlantic. Also helped organize an Analytics Guild - a 7 week training workshop for SQL beginners.

San Francisco, Ca, Us

• Selected to participate in Lyft's 8-month Machine Learning Mastery Program, designed for engineers, data scientists, and analysts to study Machine Learning through mentorship and hands-on, Lyft-oriented projects. The goal is to parallelly develop and apply learnings to enhance daily job function.• 15th team member, 3rd woman and 2nd analyst in the company to graduate from the program. 1st person to complete in under 6 months.• Topics covered: Statistics, Linear and Logistic Regression, Model Regularization, Cross-validation, Data Imputation, Imbalanced Classes, Time Series, Image Processing, Decision Trees, Deep Learning (Neural Networks), Model Testing and Deployment.• Sample projects included: Forecasting demand, predicting missing locations data, estimating ride conversion, determining fraud likelihood, MNIST image recognition, sound classification with UrbanSound8K (using CNNs), predicting future rides (using RNNs).

San Francisco, Ca, Us

• Organized Lyft and competitor data to incorporate key metrics into a weekly market tracker with digestible market health insights, key levers to reduce softness, and actionable recommendations for the Mid-Atlantic leadership team.• Extracted and wrangled spatial data from venue JSONs/geojsons using PrestoSQL and Python to create monitoring for time-sensitive, unstructured events (concerts, protests, flash mobs etc.). Created meaningful visualizations to communicate traffic patterns around this new venue type, and inform real-time adjustments of pins and optimal venue placement.• Used linear regression to forecast the growth of Lyft’s Halo ad display installations and number of ad hours played. Developed reporting to arm the Halo team with business metrics like inventory count, device utilization, activation rate etc. to track the health and status of installed units.• Applied segmentation to analyze the hyperlocalized commute ridership in Lyft's core East markets, creating a dashboard that pin-points areas where we can surgically increase driver-side incentives and reduce rider wait time. Surfaced 78K in ride opportunity and $1.1M in bookings potential across DC, BOS and PHI. • Conducted deep-dive of the supply/demand imbalance on Naval Bases in Norfolk. Developed model to predict optimal driver acquisition volume and velocity based on current driver behavior and desired ETA. Surfaced a $500K+ incremental monthly bookings opportunity for 6 bases in the Norfolk area, and implemented an education campaign to expand driver exposure to Bases.

Reston, Va, Us

• Managed monthly data production and QA for Comscore’s cross platform syndicated XMedia product to ensure timely and accurate data deliveries to clients. Automated data validation processes to predict data anomalies and production chokepoints, reducing delivery turnaround time by 30%. • Worked cross-functionally with Product, Engineering and Analytics teams to develop new product features and improve existing methodology for our Cross Platform Extended TV (ETV) product. • Performed robust data investigations on XMedia and ETV by analyzing complex datasets using PostgresSQL, Python, Scalar, PySpark, R, and Pig. Created interactive dashboards to surface data driven strategies, and provided actionable recommendations to the Executive Team.

Dallas-Fort Worth, Texas, Us

• Collaborated with AAdvantage and Operations Research teams to methodically identify future high value customers. Cleansed and validated data to build predictive models using SQL and R.• Leveraged AAdvantage Redesign 5.0's automation capabilities to understand individual traveler behaviors and unbundle promotional benefits. Provided corporate travelers with targeted and personalized loyalty program offerings to incentivize incremental bookings.• Defined concrete, actionable steps to streamline the Sales challenge process. Reduced lead time due to manual data scrubbing, and offered real-time integration on aa.com between challenge registration and enrollment.

Dallas-Fort Worth, Texas, Us

• Monitored and analyzed revenue and passenger data in 5 key American hubs (MIA, DCA, CLT, PHL, PHX) to identify drivers of corporate loss. Created Tableau performance dashboards and recommend policies to help improve operational performance and capture revenue share.• Simultaneously planned and managed 3 promotional initiatives aimed at enhancing corporate traveler loyalty from start to finish. Worked closely with interdepartmental stakeholders to identify and enroll 10,000+ targeted audiences per cycle• Developed AAVacations partner email promotions to offer vacation package discounts to corporate accounts with large leisure spend. Tracked and evaluated accounts' usage to better orient this program's benefits, resulting in a 20% increase in corporate enrollment rate• Redesigned the new-hire training and development process to align with SVP's corporate imperatives• Designed, implemented, and interpreted a trilingual consumer research survey to help Executives visualize AA’s customer sentiments year-over-year. Expanded the targeted audience base by 16% and increased response rate from 18% to 32%

Durham, North Carolina, Us

• Balanced 25+ hours of editorial and design commitment with schoolwork each week. Managed and prioritized simultaneous responsibilities• Coordinated with online editors to cohesively package the newspaper. Met tight graphics deadlines• Provided daily Photoshop and InDesign training to prepare new designers for leadership as Associates• Brainstormed ways to design and manage advertisements to meet client specifications. Laid out page templates for daily ads

New York, Us

• Assessed Ralph Lauren’s competitive advantage in the fashion industry through conducting 100+ hours of competitor analysis and examining brands, product categories, suppliers, ship mode, ordered units etc. in Ralph Lauren’s $2 billion portfolio• Performed due diligence on 3 countries of origin for Ralph Lauren to enter. Provided the Global Manufacturing and Sourcing Team with recommendations for future business expansion • Designed and developed an omni-channel activation plan to raise Ralph Lauren’s brand awareness as the official Team USA sponsor, and drive Olympic Wear sales in the 100 days leading up to the Rio 2016 Games. We suggested the concept of "Snapshot to Buy," which would allow customers to take a screenshot of desired products on Snapchat and be taken to the product's Ralph Lauren Store landing page. The idea received wide acclaim and gained traction with David Lauren and a panel of 12 VPs/Directors during our presentation; the following summer, a similar "Shoppable Photos" idea was adopted on the company's Instagram account

Hk

• Published a 48-page research report on ramifications of minimum wage in closing Hong Kong’s gender-wage gap• Analyzed statistical data to provide a gender-wage analysis by occupation, age and place-of-birth from 2006 to 2012• Conducted field research to observe non-wage societal effects of minimum wage implementation on low-income women• Provided policy recommendations on ways the government and major stakeholders can practice gender mainstreaming to end occupational segregation and expand employment for women

Hong Kong, Cn

• Chaired Jebsen’s corporate rebranding initiative. Worked directly with Jebsen’s Group Human Resources Director to redesign infographics and promotional products to highlight company’s core values• Collaborated with departments to identify programming strategies for Jebsen’s Managerial Town Hall Meeting. Served as lead thematic designer for the event, and created a "journey" graphic to present to the company Chairman• Initiated and taught a Prezi learning and development workshop to 20+ department managers and staff

Bachelor'S Degree

Education record