# Kenneth L. > Software Engineer, Data Scientist Location: United States, United States Profile: https://flows.cv/kennethl • Software engineer & data scientist with 10+ years of experience with big data, statistics, machine learning, deployment of data science solutions and software development • Significant research experience as demonstrated by awards, publications and presentations • A versatile team player with a track record of quick execution and quality delivery Specialties: Big Data, Statistics, Machine Learning, Hadoop, JavaScript, Python, R, Distributed Processing, Data Mining, A/B Testing, Analytics, Web Development, Search Quality, Automation ## Work Experience ### Staff Software Engineer @ Wheel Jan 2022 – Present | San Francisco Bay Area Web development of the virtual healthcare platform ### Staff Data Scientist @ LinkedIn Jan 2019 – Jan 2020 | San Francisco Bay Area • Curated a business metric of engaged LinkedIn Premium subscribers, demonstrating its causal impact on subscription renewal. The metric identifies key product features with actionable insights, and has been used to benchmark all cross-functional strategies from sign-up targeting, onboarding, feature recommendation to retention • Led a tiger team to deliver daily executive summary during the onset of the pandemic about its impact on LinkedIn business, and propose data-driven mitigation strategies, managing the balance between timely delivery, resource availability and analytic rigor • Team lead to drive initiatives to improve the user experience, growth and retention of the paid Premium subscription service via experimentation and machine learning methods ### Data Science Manager @ Facebook Jan 2018 – Jan 2019 | San Francisco Bay Area • Developed a Facebook user segmentation model based on users' behavior and attitude. User segments identified as high potential for product growth have been used for audience targeting in the Facebook repositioning campaign, in paid group subscription service, and in product recommendation features • Managed a team to drive initiatives of behavioral and sentiment studies of Facebook group admins and group members, providing insights about areas most needed for product enhancements, behavioral signals predictive of churn, and the optimal timeframe to act proactively to improve retention • Built predictive models of users' perception of Facebook as well as interests. Models have been validated about their predictive power, and used in personalizing messages for group activation ### Senior Software Engineer @ Apple Jan 2015 – Jan 2018 | San Francisco Bay Area Technical lead to drive all aspects of search quality valuation including both online testing and human judgment, from backend development, launching live experiments, to presenting test results. In charge of evaluating products including AppStore, Apple Music, iTunes, HomePod, Apple TV and Siri • Spearheaded the engineering effort to extend the capability of in-house A/B testing infrastructure to evaluate the impact of advertising on AppStore, and published reports post-launch • Pioneered success metrics for Apple Music search and new iOS 11 features in AppStore • Led the evaluation of how site speed performance impacts user engagement and conversion • Engineered automated pipelines to benchmark Siri search performance before HomePod product launch • Produced A/B test readouts to drive launch decisions for search algorithms including query refinement, topic modeling, signal boosting and machine-learned weights for ranking signals • Designed and executed an evaluation plan to compare the search relevance of AppStore with competitors ### Staff Data Scientist / Software Engineer @ eBay Jan 2011 – Jan 2015 | San Francisco Bay Area • Developed clustering methodology to personalize timing for sending push notifications, delivering significant engagement improvement (50%+ lift in click-through rate; 10% lift in mobile traffic) • Spot Award for pioneering experimentation of the notification service on the mobile platform, and for delivering significant improvement in user engagement • Developed an automated pipeline to monitor the quality of eBay category recommendation engine by computing sellers’ acceptance rates in creating listings • Deployed scalable, in-house machine-learning solutions in distributed systems to address high-value business questions • Improved lift estimation in A/B testing by means of mixture modeling coupled with bootstrapping • Accelerated A/B test report generation by 80% on the experimentation platform, implementing in-database computation • Built a web application to access the Data Warehouse to retrieve the activity log of any eBay user ### Postdoctoral Senior Fellow @ University of Washington Jan 2009 – Jan 2011 • Developed supervised methodology based on Bayesian model averaging of regression models to construct genetic networks from high-dimensional genetic data • Pioneered robust mixture models to identify cell populations, and developed a publicly available R software package (110,000+ downloads to date) ## Education ### PhD in Statistics The University of British Columbia ### MPhil in Statistics & Actuarial Science The University of Hong Kong ### BSc in Actuarial Science The University of Hong Kong ## Contact & Social - LinkedIn: https://linkedin.com/in/kenchlo - GitHub: https://github.com/kenchlo2 --- Source: https://flows.cv/kennethl JSON Resume: https://flows.cv/kennethl/resume.json Last updated: 2026-04-12