Frances Huang Email & Phone Number

San Francisco, California, Us

DS lead on Rider Core, working on consumer experience and engagement, and user segmentation.

San Francisco, Ca, Us

DS Lead on Rider Travel (Scheduled Rides, Airports, and Travel Growth) and pre-request (Core Experience).

Menlo Park, Ca, Us

Instagram Relevance, Creator Ranking: January 2022 - July 2023; Messenger Kids and Youth Platform, Growth Ranking: July 2020 - January 2022- Pioneered and optimized ranking strategies for valuable Creator content distribution, and worked with ML engineers to launch a boost for “healthy Creators” that powered a 20% increase in Creators’ follower growth and reach- Investigated and presented critical data insights on IG Creators’ production and distribution trends to IG leadership; improved the pricing efficiency of the Creator incentives program by 10% and production retention by 4.5% with ranking-based selection criteria and tiered payout structure - Leveraged advanced experimentation (boosting, inventory deletion, cluster test, mixed experimentation) and causal inference to evaluate the ecosystem value of Creator content and Creator-to-Creator network effect, to define the org-wide network sessions measurement framework, and to identify graph-based ranking levers that eventually drove a 5% increase in Creator production - Led a cross-functional team of 20 engineers, designers, and user researchers to persuade senior product leadership to pivot and invest in a redesign of the Messenger Kids new user onboarding experience, effectively reducing onboarding drop-offs by 20% and generating 300k MAU growth - Established the author-side holdout measurement framework and experimentation guideline for the entire Instagram Relevance org (10 ranking teams); drove alignment across 20+ stakeholders from 4 teams on the metric tradeoff framework for Creator topline and operational metrics to streamline 30+ launches - Upleveled the DS teams ’ analytical rigor by facilitating the weekly peer review forum for 20+ IG Relevance data scientists, formalizing team-wide analytical best practices, and mentoring and onboarding 5+ data scientists and 10+ engineers

Boston, Ma, Us

Data Analytics and Project Management: • Collaborated closely with leading industry experts and senior staff to construct econometric and quantitative models to support clients in high-stake litigation matters; • Led the drafting of memos and presentations for clients summarizing the methodology and errors found by our team and prepared the experts for trial testimonies • Directed and oversaw teams of consultants to develop regression models and machine learning algorithms with over 2TB of data to predict pricing and investigated anti-competition practices among airline companies• Modeled security trading behavior in R and SAS to estimate class action damages• Designed, fielded, and analyzed complex experimental studies and to deliver insights on consumer behavior and assess damages in multi-million lawsuits against major telecommunication providers • Spearheaded and launched an interactive dashboard using R Shiny to restructure a survey and legal opinions database and to automate the querying and reporting process, resulting in a 30% increase in research efficiencyLeadership and Firm Development: • Led firm-wide training sessions on R, Stata, SAS, SQL, and statistical sampling for MBA/PhD-level associate consultants; served as the statistics and programming mentor for the office • Presented on behalf of the firm at various career fairs, recruiting events, and leadership conferences• Interviewed and evaluated prospective analyst candidates and participated in debriefing meetings

Boston, Ma, Us

Washington, District Of Columbia, Us

• Innovated and optimized data analytics by unprecedentedly creating a customized R package from scratch(scrivizlake) that streamlines data transformation and visualization; contributed to a 65% increase in research productivity • Managed, manipulated, merged, and processed large and complex datasets and performed statistical weighting and analysis using R and SPSS in a fast-paced work environment• Applied predictive modeling and machine learning methods to model voting behavior and design data-driven strategies for political campaigns• Regularly attend research panels, workshop, webinars about voter modeling and prediction by the Urban Institute, the Analyst Institute, and the Catalist and author briefings for senior analysts

Bachelor'S Degree, Statistics, Political Science

Exchange Program: Certificate In Social Sciences, Economics; International Relations

Summer Session

High School