Senior Data Scientist with 11+ years of experience applying machine learning, statistical modeling, and data-driven experimentation to solve complex problems across fintech, education, and civic technology domains. Proven expertise building predictive models, designing data pipelines, and deploying ML systems at scale, with a strong background in LLM-powered applications, feature engineering, and data analysis to deliver measurable improvements in performance, automation, and decision-making. Experienced in designing end-to-end analytics workflows for large-scale voting and transactional datasets, developing predictive analytics to simulate system performance under varied load scenarios, and implementing ML-based monitoring/alerting to reduce incident detection time. Also has experience across finance fraud detection and anomaly classification, and building recommendation/ranking systems and predictive personalization models to improve engagement, discovery, and product metrics.

Kevin S Hen

Senior Data Scientist with 11+ years of experience applying machine learning, statistical modeling, and data-driven experimentation to solve complex problems across fintech, education, and civic technology domains. Proven expertise building predictive models, designing data pipelines, and deploying ML systems at scale, with a strong background in LLM-powered applications, feature engineering, and data analysis to deliver measurable improvements in performance, automation, and decision-making. Experienced in designing end-to-end analytics workflows for large-scale voting and transactional datasets, developing predictive analytics to simulate system performance under varied load scenarios, and implementing ML-based monitoring/alerting to reduce incident detection time. Also has experience across finance fraud detection and anomaly classification, and building recommendation/ranking systems and predictive personalization models to improve engagement, discovery, and product metrics.

Available to hire

Senior Data Scientist with 11+ years of experience applying machine learning, statistical modeling, and data-driven experimentation to solve complex problems across fintech, education, and civic technology domains. Proven expertise building predictive models, designing data pipelines, and deploying ML systems at scale, with a strong background in LLM-powered applications, feature engineering, and data analysis to deliver measurable improvements in performance, automation, and decision-making.

Experienced in designing end-to-end analytics workflows for large-scale voting and transactional datasets, developing predictive analytics to simulate system performance under varied load scenarios, and implementing ML-based monitoring/alerting to reduce incident detection time. Also has experience across finance fraud detection and anomaly classification, and building recommendation/ranking systems and predictive personalization models to improve engagement, discovery, and product metrics.

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Work Experience

Data Scientist / Software Engineer at Voting Works
February 1, 2023 - Present
Designed and implemented data pipelines and analytical workflows for large-scale voting system datasets, improving processing efficiency by ~30%. Built statistical models and anomaly detection systems to identify irregular voting patterns and system inconsistencies. Developed predictive analytics tools to simulate system performance under varying load and edge-case scenarios. Conducted EDA and hypothesis testing to improve system reliability and validation accuracy. Implemented ML-based monitoring and alerting systems, reducing incident detection time by ~30%. Collaborated with engineering and security teams to ensure data integrity, auditability, and compliance.
Data Scientist / Software Engineer at Stripe
June 1, 2019 - November 1, 2022
Built machine learning models for financial data analysis, including fraud detection and transaction anomaly classification. Developed feature engineering pipelines to improve model performance and reduce false positives by ~20-25%. Designed and optimized data pipelines for large-scale transaction data, improving processing throughput by ~20%. Performed A/B testing and experimentation to evaluate product features and optimize financial workflows. Created data dashboards and reporting tools for internal stakeholders, improving visibility into key business metrics. Applied statistical analysis and predictive modeling to improve decision-making in payment workflows.
Data Scientist / Software Engineer at Clever Inc.
July 1, 2014 - April 1, 2019
Built and deployed recommendation and ranking systems for the Clever Library marketplace, improving user engagement and discovery. Designed data models and analytics pipelines supporting thousands of daily users and transactions. Conducted user behavior analysis and cohort analysis to improve product adoption and retention. Developed predictive models to optimize content ranking and personalization strategies. Performed A/B testing and experimentation, improving feature effectiveness and UX outcomes. Collaborated with product teams to translate data insights into product decisions and roadmap improvements.

Education

B.S.E. (Bachelor of Science in Engineering) at University of Pennsylvania
January 11, 2030 - August 26, 2026
Study Abroad Program at University of Otago
January 11, 2030 - August 26, 2026

Qualifications

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Industry Experience

Financial Services, Education, Other, Software & Internet