# Stanley Wang > Senior Software Engineer Location: San Francisco, California, United States Profile: https://flows.cv/stanleywang My expertise and experience is in distributed backend services and systems in the domains of insurance, finance/payments, and online advertising. This includes domain-driven design and modeling, defining REST APIs and interfaces, implementation, handling distributed failure scenarios, and maintaining backwards compatibility. I am also familiar with the foundations of machine learning and data pipelines/infrastructure. ## Work Experience ### Senior Software Engineer @ Affirm Jan 2024 – Jan 2025 | San Francisco, California, United States Engineer on Identity Data team, which manages and enforces the integrity of the core user data model. Projects (using Python, AWS, Protocol Buffers, Airflow, Snowflake): * Designed and implemented a full migration of 121K users to a new user unique identifier model in Canada to significantly reduce tech debt and move every user onto a more robust and accurate user identification system while improving identification latency by 10%. * Orchestrated safe regular upgrades of a critical phone number library to capture new revenue of several 100s of new users per week. * Improved key user and billing checkout-critical API latencies by up to 20%. ### Senior Software Engineer @ Hippo Insurance Jan 2020 – Jan 2023 | Palo Alto, California, United States Tech lead for Salesforce integration of sales agent workflows. Led a team of 4 engineers to complete cross-functional projects that collaborated closely with business teams. Heavily involved in managing the team roadmap, working out project requirements, drafting technical design documents, mentorship, and doing project management. Projects (using JavaScript/TypeScript, Node.js, AWS, GCP, Salesforce): * Redesigned and implemented distributed data sync pipelines between Salesforce and internal systems for all insurance leads, policies, and other core data to address key idempotency/duplication issues, greatly improve reliability, and align with our target microservice architecture. * Designed and implemented a new service and async pub/sub worker for new claim management and payment processes in Salesforce. This integrated insurance policy coverages and deductibles from separate internal systems to unify inside Salesforce and make available for paying out all customer claims. * Redesigned and migrated pipeline for transactional billing email processing (hundreds of thousands per month) from the monolith to a new event-driven system with a service and worker. This improved correctness, reliability, and observability while significantly reducing tech debt and paving the path for other modernization efforts. * Addressed numerous regulatory compliance issues across claims and core insurance products in collaboration with business teams through scripts and infrastructure work to comprehensively solve issues with no regressions, including ~400k data issues for an agent license validation problem and thousands of claims needing catastrophe code classification. ### Senior Software Engineer @ Yelp Jan 2015 – Jan 2020 | San Francisco, CA Engineer on Ad Syndication and Revenue teams. Played a major role in scaling up the syndication retargeting product from an MVP, and contributed to a variety of key financial reporting and revenue recovery initiatives on the Revenue team. Heavily involved in drafting technical design documents, mentorship, and project management. Projects (using Python, AWS, Kafka): * Modernized revenue-related financial reporting by migrating critical financial tables to a real-time Kafka-based data pipeline and data lake, with high performance (up to 2k events/sec) through use of PyPy. * Led the scale-up of a major new ads retargeting product from $30K to $1.6M in monthly revenue. * Modernized and refactored the ads retargeting pipeline for selecting campaigns and budgets to use on external partners, representing $X millions of dollars in revenue per month, to significantly improve reliability and support future improvements while ensuring no negative revenue impact. * Created new AWS-based workflow infrastructure to support advertiser installment plans and recoup revenue from delinquent advertisers, by reducing advertiser churn and chargebacks through more optimized schedules for collection attempts. This resulted in $X millions of dollars in recovered revenue. ### Data Scientist @ Backplane Jan 2014 – Jan 2015 | San Francisco, CA Data scientist/machine learning engineer on the Data team. Projects: * Productionized new logging infrastructure to schematize and ensure consistency of structured log data * Oversaw analytics and machine learning systems using Amazon Elastic MapReduce (EMR) and Apache Spark * Defined and implemented metrics to track community size and quality ### Forward Deployed Engineer Intern @ Palantir Technologies Jan 2013 – Jan 2013 | Palo Alto, CA * Palantir Phoenix search optimization * Investigated several solutions including better cache utilization and query term reordering ### Software Engineer Intern @ Facebook Jan 2012 – Jan 2012 | Menlo Park, CA * Ads Infrastructure team: performance optimization of ad search indices * Significantly reduced latencies (by 21-75%) for ad queries to the ad indexer system, removed concurrency bottlenecks, and built an offline analysis tool for optimal search index generation ### Data Abstractions Class TA @ University of Washington Jan 2012 – Jan 2012 | Seattle, WA ### Software Engineering Intern @ Ning Jan 2011 – Jan 2011 | Palo Alto, CA * Analytics/Infrastructure teams: website performance monitoring, email alert framework and DSL ## Education ### Bachelor of Science (B.S.) in Computer Science University of Washington Jan 2010 – Jan 2014 ## Contact & Social - LinkedIn: https://linkedin.com/in/stanleynwang --- Source: https://flows.cv/stanleywang JSON Resume: https://flows.cv/stanleywang/resume.json Last updated: 2026-03-22