# Daniel Hwang > Sr. Software Engineer at Tinder Location: San Francisco Bay Area, United States Profile: https://flows.cv/danielhwang2 Software & Data Engineering, Distributed Systems, Cloud Infrastructure (AWS, Azure), Data Science, Bioinformatics ## Work Experience ### Software Engineer @ Tinder Jan 2025 – Present | Palo Alto, California, United States ### Software Engineer @ Microsoft Jan 2021 – Jan 2025 | Mountain View, California, United States Bing, Whole Page, WebXT Working on the base layer data for answer and knowledge card in Bing. • Increased data coverage and quality by onboarding data, crowdsourcing curation, and rebuilding the knowledge graph. Designed and implemented scalable data pipelines to replace obsolete or absent data with new resources. Optimized and generalized prompts with Large language models(LLMs) for data parsing, sourcing and validation. Led projects by coordinating multiple teams' requests. • Developed a data coverage and quality measurement system for leadership, PMs, and data owners to facilitate data-driven business decisions. Dashboards effectively visualize large amounts of data with tables and graphs. Led whole project across multiple stakeholders, including data owners, PMs, leadership, crowdsourcing teams, and development vendors. • Leveraged LLMs, crowd sourcing, A/B testing, etc. ### Software Engineer @ Amazon Web Services (AWS) Jan 2021 – Jan 2021 | Palo Alto, California, United States Worked on AWS services - • Utilized cloud services to design and implement scalable system – data pipelines, software UI changes, environment set up using Active Directory authentication across OS, etc. • Mentored a 2021 summer intern, finalizing and deploying their work to production. ### Bioinformatics Scientist - Software Engineer @ Thermo Fisher Scientific Jan 2018 – Jan 2021 | Greater Los Angeles Area One Lambda, Transplant Diagnostics Worked on overall data system for Transplant Diagnostics Kits. • Designed and built NGS(Next Generation Sequencing) data process integration system (Pipeline) with Python and C# • Developed classification model to predict primer set amplifying status using Python pandas, numpy and scikit-learn • Designed and developed internal HLA sequence library software using Python and C++ • Updated internal database regularly by collecting, cleaning and validating data from various sources • Developed multiple Python programs to improve data processing (Workflow automation) • Maintained multiple software written by R, Python • Implemented data conversion software to support laboratory scientists with C# • Generated and updated technical specific documents for customer-facing products ### Student Software Engineer @ USC Norris Comprehensive Cancer Center, Bioinformatics Research Jan 2017 – Jan 2018 | Los Angeles, CA, USA Worked for Bioinformatics research group to help professors from Biology domain. • Automated multi-step analysis pipelines (Gene sequencing tools) on Linux environments with Python • Generated heatmap, scatter, cluster plots, etc. to visualize data with R • Revised scripts from existing R packages (Cell Ranger, Monocle, Seurat, etc.) to handle varying biologist requests • Analyzed NGS data and single cell RNA-seq data from wet laboratories with R and Python. ### Bioinformatics software engineer intern @ Thermo Fisher Scientific Jan 2017 – Jan 2017 | Woodland Hills, CA, USA • Designed and implemented HLA (Human leukocyte antigen) sequence library processing tool with C++ • Above tool automates data processing, validates and integrates HLA sequence alignment data • The tool confirms the consistency and quality of HLA sequences • Reduced current process from 2 weeks to under 5 minutes and from 3 people to 1 person ### Student Researcher / Researcher @ Data mining & Bioinformatics Laboratory Jan 2013 – Jan 2017 | Gachon University, Republic of Korea • Published 5 pharmaceutical data related publications, 2 breast cancer data related publications, and presented 1 poster • Developed computational methods to predict drug side effects and breast cancer prognosis • Extracted classifiers, recognized unique data patterns, and verified experiment results with various evaluation methods • Implemented Data Preprocessing programs (converting raw data into usable data format), Graph Search Algorithms, Classification Models, and Performance evaluation programs (Cross-validation) with C++ and R • Applied various statistical methods to generate rules for classifiers • Conducted several machine learning experiments with Weka • Participated in junior assistants’ researches as a second author by guiding their research process, contributing programming and data processing *** PROJECTS FOR RESEARCH *** 1) Identified gene networks of drug side effects and developed a computational method to predict side effects based on biology and pharmacological data • Extracted gene networks of side effects and predicted potential side effects by utilizing side effect genes, drug features, and protein-protein interaction (PPI) networks. Obtained statistically meaningful p-values (< 0.01) for gene networks of side effects, and improved AUC values (Average: 0.73) for the classification model 2) Developed a classification model to predict prognosis of breast cancer patients • Identified breast cancer prognosis-specific gene network using gene expression data and PPI data. Extracted the network by comparing correlation coefficient scores between ‘Good prognosis’ and ‘Bad prognosis’ patients. Classification performance of this model is improved as compared with previously published studies. Performed gene ontology enrichment analysis on the prognosis-specific network ## Education ### Master of Science (M.S.) in Computer Science University of Southern California ### Bachelor of Engineering (B.E.) in Computer Science Gachon University ## Contact & Social - LinkedIn: https://linkedin.com/in/daniel-hwang-y --- Source: https://flows.cv/danielhwang2 JSON Resume: https://flows.cv/danielhwang2/resume.json Last updated: 2026-04-11