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Ruijing Wang
Intern Data Scientist specializing in healthcare AI and experimentation
Boulder, COData Scientist Intern1 years experienceInternHealthcareDigital HealthHealthcare IT
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About
Human-AI Design Lab practitioner who productionized a wearable-health anomaly detection system by evolving a standalone autoencoder into a hybrid autoencoder + GPT-based approach, backed by PySpark ETL and MLOps on AWS SageMaker/MLflow. Also has applied LLM troubleshooting experience (fine-tuned FLAN-T5 summarization) and partnered with BI teams to run A/B tests and improve retention via feature stores and experimentation.
Experience
Data Scientist InternEchoPlus AI
Research ScientistHuman-AI Interaction Design Lab
Education
Stevens Institute of Technologydoctorate, System Engineering (2025)
New York Universitymaster, Computer Engineering (2021)
Hebei University of Technologybachelor, Electrical Engineering & Automation (2018)
Key Strengths
- Took an anomaly detection prototype to production for wearable health data
- Built scalable PySpark ETL pipelines for multivariate time-series ingestion and alignment
- Implemented MLOps workflows using AWS SageMaker and MLflow
- Reduced production latency by redesigning pipelines for real-time/batch processing
- Diagnosed LLM workflow issues using layered triage (infra health to logic/alignment)
- Resolved fine-tuned FLAN-T5 summarization inconsistencies via trace-based debugging plus prompt/vocab/fallback changes
- Effective technical communication via architecture-focused demos and trade-off discussions
- Enabled product experimentation by building feature stores supporting A/B testing and retention modeling
- Delivered measurable impact: larger milestone rewards increased user retention
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