Senior data scientist

David Sung

Senior Data Scientist

********@******.***.*** 415-***-**** San Francisco, CA

Profile Summary

Mastercard San Francisco, CA

Associate Technical Product Manager, PM Transition Program Jan. 2022 - Present

● Led the enhancement of Mastercard's Smart Authentication model within the EMV 3-D Secure system, analyzing data trends to guide project direction, improving security and UX through innovative technology applications.

● Led a cross-functional team of 15 professionals including Product Managers, Data Scientists and Data Engineers through the entire Product Development Life Cycle by meticulously planning, managing risks, and ensuring adherence to quality standards.

● Addressed regional model variations using data validation and labeling strategies, leveraging Apache Hive, Pandas and Statistical Analysis techniques like hypothesis testing and predictive modeling, resulting in a 95% fraud detection rate, a 20% increase in global customer satisfaction, and an estimated $10 million annually in preventing fraud.

Senior Data Scientist Mar. 2019 - Present

● Led the Smart Authentication Airflow Project, driving data-driven decision-making in product development by implementing automated data reporting processes that streamlined data workflows, while managing over 30 diverse DI

(Decision Intelligence Model) work requests, optimizing workflows and enhancing customer satisfaction.

● Liaised closely with Marketing, Sales, and Engineering teams to translate data insights into actionable strategies that align cross-departmental goals with product objectives.

● Leveraged advanced statistical tools and techniques, such as Python and SQL for data manipulation, complemented by A/B testing, logistic regression analysis, and decision tree modeling, to analyze credit/debit card transaction data. This analysis generated insights that shaped strategic product decisions and influenced feature prioritization.

● Designed and interpreted A/B tests using Google Optimize and Optimizely, and employed experimental frameworks like Bayesian testing and factorial design, that validated product hypotheses, driving improvements in card authentication/authorization models and enhancing user experience based on data-backed evidence. Professional Experience

Engagement, Agility, Growth Mindset, Persuasion, Influence, Taking Initiative, Empathy, Building Inclusion, Listen to Feedback Soft Skills: Problem Solving, Analytical Thinking, Communication Skills, Team Collaboration, Attention to Detail, Stakeholder Planning and Execution

Methodologies: A/B Testing, Experimental Design, Qualitative/Quantitative Analytics, Data-Driven Decision Making, Strategic Distributions, Causal Inference, Statistical Data Analysis, Data Mining, Predictive Modeling, Time Series Analysis Statistical Analysis: Hypothesis Testing, Regression Analysis, ANOVA, Probability Theory, Conditional Probability, Probability Visualization Tools: Tableau, Power BI, Looker

Big Data Tools: Apache Airflow, Apache Hive, Presto, Apache Hadoop, Apache Kafka, Apache Zookeeper, Gobblin, Apache Sqoop Monitoring Tools: Prometheus, Grafana, Elastic Stack Data Storage: AWS Redshift, MySQL, PostgreSQL, Oracle, Hadoop Distributed File System (HDFS) ETL Tools: AWS Glue, AWS Data Pipeline

Machine Learning: XGBoost, TensorFlow, Scikit-learn, Linear Regression/Logistic Regression, Clustering, Decision Trees Data Processing Frameworks: Apache Spark, Databricks Programming Languages: Python (Pandas, PySpark, Numpy), SQL Technical Skills

priorities to drive progress under aggressive time constraints.

● Engaged collaborator with strong interpersonal skills, able to influence and align multiple teams with conflicting management to consistently deliver exceptional results.

● Proven ability to understand user needs and align product development strategies, through meticulous project models to significantly improve accuracy and reduce false positives.

● Extensive experience with machine learning tools like XGBoost and Scikit-learn, having developed fraud detection enhancing data workflows for optimal performance.

● Skilled in big data frameworks such as Apache Spark and AWS Glue, excelling in building robust data pipelines and enhance data-driven decision-making for innovative solutions. in employing machine learning and product analytics to analyze data trends, inform product direction, and

● Solid technical skill set with advanced proficiency in Python, SQL, and data visualization tools like Tableau, skilled directly impact strategic business decisions.

● Senior Data Scientist with a demonstrated ability to leverage data analysis and modeling for actionable insights that

● Analyzed user behavior data with tools like Mixpanel and Amplitude to uncover actionable insights using methodologies such as cohort analysis and churn prediction, guiding product enhancements that align with user needs and improve user engagement and retention in our card authentication/authorization systems.

● Presented proof of concepts to customers using blind data from production servers to showcase model efficacy in fraud detection, effectively translating complex data findings into understandable visual representations and rebuilding fraud detection models with new features upon significant changes in customer spending behavior.

● Developed and monitored key performance indicators for data initiatives using Prometheus, Grafana, and the Elastic Stack, and visualized through Tableau, Power BI, and Looker, resulting in comprehensive monthly reports highlighting fraud prevention savings, authentication friction, and decline rates for executive management.

● Oversaw the implementation of data governance policies and compliance with data protection regulations, ensuring the security and privacy of sensitive data across all platforms.

● Actively engaged in continuous professional development by attending workshops on Advanced Machine Learning and Predictive Analytics, pursuing certifications such as Certified Analytics Professional (CAP) and the Data Science Certification from Coursera, and exploring cutting-edge data science techniques like deep learning and ensemble methods to bring innovative solutions back to the team. Key Deliveries:

● Processed large volumes of transactional and authorization data using scalable data solutions to ensure secure storage, accessibility, and data integrity.

● Developed automation scripts with Python and SQL for anomaly detection utilizing moving averages and standard deviation analysis to clean and preprocess data by calculating the 7-day moving average and identifying outliers when score distribution was outside of 1.5 standard deviations, ensuring data quality and integrity for monitoring smart authentication score distribution across various regions.

● Generated actionable reports that identified root causes of score discrepancies, leading to a 20% reduction in transaction discrepancies over 6 months.

● Developed machine learning models using XGBoost and Python, enhancing fraud detection accuracy in Mastercard’s Decision Intelligence Model for all card transactions to 92% and reducing false positives by 15%, utilizing transaction data, fraud detection data, cardholder data, device data, and merchant data sourced from internal fraud detection systems and transaction monitoring systems, using machine learning model training and algorithm optimization techniques.

IMVU Data Engineer Redwood City, CA Jul. 2018 - Feb. 2019

● Developed next-generation data-monitoring tools to track the health status of various Hadoop clusters and detect data node volume failures, employing Apache Kafka for real-time data streaming, Apache Spark for analyzing these streams to pinpoint anomalies, and Apache Gobblin to integrate and manage data sources across the infrastructure. This robust monitoring setup achieved an uptime of 99.95% for critical services.

● Engineered data pipelines using Apache Airflow for workflow orchestration and AWS Data Pipeline for efficient data transfer across AWS services, ensuring data consistency and achieving a peak response time of under 100 milliseconds in critical real-time applications.

● Optimized data infrastructure operations by automating routine tasks, cleaning out storage space, and organizing tables and schemas on MySQL servers in preparation for migrating Spark/Hive jobs to the cloud, thereby reducing manual maintenance time by 15 hours weekly.

● Designed and implemented ETL processes using AWS Glue to efficiently and reliably move data across our cloud infrastructure, achieving a data throughput of 250 GB/hour from operational databases to our data lake for real-time analytics.

● Improved database performance and streamlined data pipeline operations by integrating Apache Spark for rapid data processing, using Presto for low-latency data querying across heterogeneous sources, and optimizing AWS Redshift for efficient large-scale data warehousing. These enhancements collectively reduced query execution times by 40% and streamlined data infrastructure management.

● Developed a comprehensive monitoring system using Prometheus for collecting metrics, Grafana for visualization, and Elastic Stack for log processing, to continuously track the health status of Hadoop clusters and data pipeline tools. This integrated approach achieved an impressive average issue detection time of under 5 minutes. Facebook (now Meta) Data Engineer (Intern) Menlo Park, CA May 2017 - Aug. 2017

● Utilized Python and data tools such as Pandas and NumPy to scale memory margining processes across approximately 12.9GB of data, enhancing the performance of both 1-socket and 2-socket Open Compute Project

(OCP) server designs in Facebook's data centers. Employed A/B testing methodologies to optimize configurations, impacting billions of users and optimizing data throughput by 15%.

● Crafted high-impact visualizations in Tableau to convey the overall quality metrics of the server design, utilizing Hive SQL-like queries to extract and analyze data. Integrated results from A/B testing experiments to demonstrate comparative effectiveness of server configurations, enhancing decision-making processes.

● Achieved Facebook’s OCP debug card validation within 3 weeks by defining a test plan using hardware testing tools like Oscilloscopes and Logic Analyzers, and forming a strategic alliance with Facebook’s hardware engineers and external ODM vendors to drive the project to completion, leveraging my skills in project management and stakeholder engagement.

Advantech Senior Technical Product Manager Irvine, CA & Taipei, Taiwan Jun. 2012 - Jul. 2016

● Led the Advantech Data Center Networking and Communication Systems Launch by deploying AdvancedTCA-ATCA, MicroTCA, CPCI, and AdvancedMC–AMC technologies, achieving key performance targets and significantly enhancing client satisfaction through improved system reliability and performance.

● Initiated the project by identifying key stakeholders including the Head of Engineering (to oversee technical specifications), the Senior Supply Chain Manager (to manage component sourcing and logistics), and the Lead Sales Executive (to align product features with market demand), setting a clear vision and objectives, and assembling a multidisciplinary team, ensuring comprehensive alignment from the start.

● Developed a comprehensive project management plan, defining KPIs for scope, schedule, and cost, which directly influenced project tracking and resource allocation. Established a strategic communication plan to maintain continuous engagement and clear guidance across all project phases.

● Enhanced British Telecom's system performance by 80% in 2016 through firmware enhancement leveraging Intel DPDK, which optimized network packet processing capabilities, thereby saving a $25 million contract and solidifying a strategic partnership.

Education

Carnegie Mellon University M.Sc. in Software Engineering & Business Management Pittsburgh, PA 2016-2018 Purdue University M.Sc. in Electrical and Computer Engineering West Lafayette, IN 2007-2010 Purdue University B.Sc. in Electrical & Computer Engineering (Minor: Mathematics) West Lafayette, IN 2003-2007 Certifications

Project Management Professional (PMP)® Certification Mar. 2024 Patents

Systems and Methods for Computing Travel Options Jan. 2023

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